Alberto Cavallo's Curriculum

Alberto Cavallo’s Curriculum

Associate Professor, Automatic Control Group
General Informations
       Alberto Cavallo was born in Napoli (Italy) on March 16th, 1964.
       In 1989 obtained the Laurea Degree at the University of Napoli "Federico II" with Laude, discussing
        the thesis "Robust Stability Analysis for Linear Time-Invariant Systems", and in 1993 he completed
        the PhD discussing the thesis "A solution to tracking problems via sliding manifolds".
       Alberto Cavallo has served as a research associate first, at the Second University of Napoli, next as
        an Associate Professor, initially at the University of Sannio, and currently again at the Second
        University of Napoli.
Research Activities of Alberto Cavallo
The research activity of Alberto Cavallo covers different aspects of the Automatic Control Theory, with
applications ranging from aerospace and aeronautic fields to robotics, civil engineering and analysis of
medical data. He has been involved in different national and European research projects, and has served as
a reviewer for the most prestigious journals and conferences of the field (IEEE Transactions on Robotics and
Automation, IEEE Transactions on Automatic Control, SIAM Journal on Control and Optimization,
Transactions on Control System Technologies, IEEE Transactions on Systems, Man and Cybernetics (Part B),
IEEE Transactions on Fuzzy Systems, AIAA Journal, Automatica, International Journal of Control, Journal of
Process Control, International Journal of Robust and Nonlinear Control, International Journal of Adaptive
Control and Signal Processing, ASME Journal of Dynamic Systems, Measurement and Control, Mechatronics,
Information Science, Fuzzy Sets and Systems, International Journal of Robotics and Automation, IET Control
Theory & Applications, Dynamics & Control, American Control Conference, ECC, CDC, AIM, CCA, VSS).

In the following, Alberto Cavallo’s research activities are detailed.

Robustness Analysis and Controller Design
The behavior of LTI systems in the presence of parametric uncertainties has been investigated. In particular,
the coefficients of the characteristic polynomial have been assumed depending linearly on some uncertain
plant parameters, thus obtaining polytopic stability regions in the parameters space. An original solution to
the problem has been proposed, computationally efficient with respect to existing methods, and a formal
unification with Kharitonov's Theorem and Edge Theorem has been presented.
Next, also nonlinearly dependent characteristic polynomial coefficients have been considered, by suitably
partitioning the parameter space into convex sub-domains.
Next, the problem of synthesizing robust controllers has been addressed, i.e. to design LTI controllers able to
maximize the "size" (according to a given norm) of the admissible uncertainties under the closed-loop system
stability constraint or under the more general constraint of closed-loop pole location within an assigned
region in the complex plane. In order to solve the problem, an original parameterization of the stabilizing
controllers has been used, and parametric optimization techniques have been employed.
Moreover, by using the same controller paramenterization, direct sensitivity reduction and simultaneous
stabilization problems have been addressed.
Finally, the problem of quadratic stability has been faced, and a method for computing the gradient and the
subgradient of the singular values of a matrix has been provided.

Tracking problems with First Order Sliding Manifold
This research topic is based on the Singular Perturbation Theory and on the Variable Structure Systems
Theory.
Tracking and regulation problems have been considered by using a sliding manifold approach. In particular,
by using the Singular Perturbation Theory, a time-varying sliding surface has been defined for the controlled
system state, and a suitable control law is defined depending on a "small" parameter ε>0.
The distinguishing feature of the methodology is that the system state always belongs to the sliding manifold,
since the initial time instant. Thus, the "reaching phase" is avoided and no peaking phenomenon can occur.
Although the proposed solution exhibits strong robustness properties, similar to high-gain control systems,
it is easy to prove the essential difference with respect to the latter: while a high-gain control strategy splits
the system state into a "slow" and a "fast" part, in the proposed approach the "fast" variable is the control,
while the whole state is "slow".
This result is obtained by a suitable (local) folding of the manifold, and considering strategies optimizing the
folding (e.g. imposing LQ functionals).
The control strategy has been applied to different systems: LTI uncertain systems, showing the high
robustness characteristics of the approach, nonlinear mechanical systems, as PUMA-like robots, and to
aerospace capsules for the attitude regulation, and to the control of electrical power systems to drive DC
motors with suitable PRM modulators, designed with a rigorous approach based on the theory of variable
structure systems.
A robust state observer has also been considered in order to estimate the controlled plant state. The observer
is and LTR-like one, modified to avoid initial peaks. Moreover, an integral term in the control action has been
introduced so as to guarantee asymptotic rejection of constant disturbances and even in the presence of
limited control gains.
Finally, since limited bandwidth actuators are unable to supply too quick control actions, control rate
limitations have been included in the controller design, and a limited control rate (first derivative) time-
varying strategy has been proposed in the same methodological framework, although retaining the strong
robustness properties of the sliding manifold approach. This solution has also been implemented on an
industrial robot Comau SMART-3 S, at the Prisma Lab of the University of Napoli "Federico II", showing a very
good accordance between simulation (theoretical) and experimental results.

High Order Sliding Manifold Approaches
Initially second-order sliding manifold strategies have been considered, in order to halve the number of
control loops required for the decentralized control of mechanical systems. The strategy has been applied to
a DC motor at the Automatica Lab of the Second University of Napoli.
The next step has been the extension of the strategy to any high order controller. The motivation is to address
output feedback tracking problems. This is the final step in the theoretical investigation of the properties of
the sliding manifold control strategy. The result shows that this kind of strategy aims at "adding zeros" to the
controlled plant, thus asymptotically bringing to zero the (finite) pole-zero excess. This gives a rigorous
mathematical formalization of the well-known technique of using "faraway poles" for derivative actions.
These results have been first presented at the World Congress of Nonlinear Analysts WCNA 2000, held in
Catania (Italy) in July 2000, within the invited speech “Sliding Manifold Approaches for the Control of Flexible
Structures”. The extension to the MIMO case has given an expression of the controller in terms of a Left
Matrix Fraction Description (LMFD), based on Markov's parameters. This approach has shown for output
feedback robustness properties similar to these for state feedback, and a systematic procedure for choosing
the controller transfer zeros has also been proposed.
By using this approach, the problem of output feedback for mechanical systems has been addressed, and
applied to the case active vibration reduction for railway car with hydraulic actuators on the bogies,
considering and analyzing different sensor locations and to a Comau SMART-3 S robot and controlling 6 dofs

with a single output centralized controller available at the Prisma Lab at the University of Napoli “Federico
II”.
The same methodology has been applied to the synthesis of sliding fuzzy controllers. In particular, high-order
sliding strategies have been considered ina fuzzy framework, resulting in the rigorous proof of the local
stability for nonlinear systems (affine in the control variable) controlled by fuzzy controllers, by using
feedback linearization and relative degree concepts. The effectiveness of the strategy has been shown in an
electric motor case and on the classical van der Pol equation.
Also, three-phase permanent magnet synchronous motors (PMSM) have been exactly modeled by a fuzzy
system, and the stabilizing action of a high-order sliding linear controller has been shown by using LMI
techniques.
Finally, switching power systems have been controlled with different high-order strategies, in particular DC-
DC bidirectional converters, for which also an estimate of the Region of Attraction (ROA) have been
computed.

Aeronautic Applications with Parametric Robustness Tools
Aeronautic applications have been addressed by using the methodologies developed for LTI uncertain
systems.
In particular, the robustness analysis algorithms have been used to find the largest region in the parameter
space so as to guarantee the fulfillment of prescribed handling qualities defined by the MIL-F-8785 specs.
Moreover, by using an original SIMO (Single-Input-Multi-Output) parameterization of the stabilizing
controllers for a given LTI plant, controllers for aeronautic applications have been designed aimed to increase
robustness and handling qualities of aircraft, stabilizing the model of the aircraft in different points of the
flight envelope (simultaneous stabilization), guarantee fault tolerance properties with respect to sensor
failures.
Moreover, active vibration control with innovative, smart materials has been considered for aeronautic
applications within European Research projects (MESA, MESEMA), see below.

Aerospace applications
In the late 1980s, the Italian and French aerospace industry investigated unmanned capsule concepts such
as the CA.RI.NA. (CApsula di RIentro Non Assistito, autonomous reentry capsule) version in 1990. Within this
application, attitude regulation during the despin phase has been addressed. The capsule was devoted mainly
to commercial microgravity experiments, and for the despin phase 20N hydrazine thrusters were foreseen
for reducing the spin. Due to the extremely complex nature of the thruster firing, a black-box time-varying
model of the thruster has been obtained, and two control phases (a rough and a fine control) have been
studied.
Next, the European Space Agency considered more economic manned solutions and started an ACRV
('Assured Crew Return Vehicle') study in October 1992. Aerospatiale, Alenia Spazio and Deutsche Aerospace
were prime contractors. Within Alenia activity, guidance, trajectory and attitude control, sensor acquisition
and filtering have been considered for the re-entry phase (from 120 km to 7 km altitude), considering
aerodynamic uncertainties and exogenous atmospheric disturbances.
Trajectory control has been carried out by using a mixed approach: a time-varying LQ controller has been
designed for the control of the longitudinal dynamics, while a VSS strategy has been selected to vary the bank
angle about a reference angle and thus controlling the latero-directional dynamics.
The above control strategy imposed large angular maneuvers to be guaranteed by the attitude controller. A
cinematic description via quaternions has been used, and a first order sliding manifold approach has been
successfully employed. Moreover, an integral action has been added in order to reject constant aerodynamic
coefficient disturbances.
The whole strategy has been tested in simulation on a MATLAB/SIMULINK detailed simulator.

Control of Smart Materials
The objective of this activity is the design of control strategies for the control of devices employing "smart"
materials, i.e. innovative materials (piezoceramics, megnetostrictives, shape memory alloys, electro-
rehologic and magneto-rehologic fluids, polymer gels, carbon nanotubes) to implement on embedded
microcontrollers, so as to realize "smart devices".
In a first phase, piezoelectric materials have been considered, a "self-sensing" circuit has been designed and
implemented, i.e. the same device acts both as actuator and sensor. From the control point of view,
collocated feedback strategies have been considered for this case. In particular a second order sliding control
strategy has given good results with an output feedback, thus avoiding the need for a state observer. a
vibration controller has been designed and implemented on a Motorola DSP board in the dSPACE rapid
prototyping environment
Next, magnetostrictive materials have been considered, and a controller has been designed in order to
compensate for the hysteresis and saturation effects. Specifically, a Preisach model has been used to
mathematically model the hystheresis, then the model parameters have been identified by using a fuzzy
identifier, finally a pseudo-compensator has been defined, such that its output signal, when fed to the
magnetostrictive actuator, makes the overall input-output behaviour (almost) linear. The analysis has been
carried out by exploiting Liptschitz properties of the Preisach operator and by using fixed-point theorems,
resulting in good prediction of the .luimit cycle, both theoretically and experimentally. By inserting the
pseudo-compensator into a position feedback control loop, a fine positioning without overshoot in the
position and peaks in the driving current has been obtained, differently from what happens without
compensator. The controller has next been implemented on a 16-bit C167 Infineon controller, and different
controllers have been connected in a CAN-based network, so as to obtain a distributed intelligent device
network.
The pseudocompensator has also been used in double control loop solution, comprising an inner force loop
and an outer position loop in order to have an accurate control of the strain and stress variable characterizing
the magnetostrictive actuator. The positioning error has been reduced to less than 1μm and reduction of
losses of 40%, due to the improved current signal driving the actuator. The above results have been extended
also to the case of variable stress.
The main application of this study has been in the noise and vibration reduction for aeronautic applications
(see below), but also biomedical applications have been considered, resulting in the organization of a session
in an international congress on the topic attended by different international experts of the field of smart
materials in medicine.
Active Vibration Control
Vibration control is a topic of great interest in the Automatic Control community. For instance, in the
aerospace field the high value of the ratio cost/payload suggests the use of lighter structures, with increased
structural flexibility. Actually, the structure is subject to the highest accelerations during the launch phase,
while in the operative phase relatively low forces are experienced by the capsule and the payload. Thus, if
the control designer is able to counteract high accelerations (even for a limited amount of time, for instance
during the launch), a less expensive solution is amenable.
Applications of flexible structure control are present in many engineering fields, from building in seismic
areas (e.g. the skyscrapers in Japan and California) to aerospace applications (solar panels, robot arms,
antennas are all flexible elements).
In some cases the flexible structure behaves like a loudspeaker, amplifying the vibrations and producing noise
as a result, as is the case of an aircraft fuselage for turboprop, where the noise is produced by the pressure
wave on the fuselage and is transmitted to the cabin.
Passive methods for vibration reduction have shown to be effective only at relatively high frequencies, since
at low frequency would require too thick passive layers, thus increasing weights. For this reason, the use of
active methods at low frequencies is crucial.

Since one of the problem to face is to avoid the excitation of unmodeled high-frequency dynamics, a first
approach has employed a limited-rate sliding control, so as to guarantee a sufficiently smooth control signal.
Next, a singular-perturbation based control strategy with state feedback has been proposed, able to operate
only in specified subspaces where the structural resonance has to be reduced, while leaving the other modes
unaffected, thus avoiding the so-called spillover effect, due to the orthogonality of the modes. Moreover, in
order to operate an output feedback, robust sliding observers have been considered. This strategy has proved
to be effective in the case of low modal density, or “well separated modes” (this concept can be defined in a
rigorous way).
This methodology has been also experimentally tested on a DC9 bulkhead, available at the Dipartimento di
Progettazione Aeronautica dell'Università di Napoli “Federico II”.
Next step has been the use of colocated control, by using piezo devices in self-sensing configuration,
mentioned above. A second order sliding strategy has been employed with satisfactory performances,
resulting in an output feedback control, so that the state observer is no longer needed.
The good results achieved have been the basis for the participation to different international research
projects, as the MESA (Magnetostrictive Equipment and Systems for more electric Aircraft) of the 5th
Framework Programme (FP) of the European Community, within the initiative “Competitive and Sustainable
Growth” and the MESEMA (Magnetoelastic Energy Systems for Even More electric Aircraft) project of the 6th
FP, participated by 18 European partners (SAAB Ericsson, ZF Luftfahart, Eurocopter Deutschland GmbH,
Alenia as end users).
Next, the problem of airborne noise and vibration on the aircraft has been considered. The problem of the
control of 2D structures (plates and aeronautic skin panels) has been considered. In this case, the high modal
density calls for a very high-order model of the structure, with experimental identification for the parameters.
An ad hoc strategy has been defined, using the experimental identification for the modes and least min
squares for the residuals. The procedure has shown to be robust from a numeric point of view.
Moreover, the identified model is structurally low-pass, that is the correct theoretical model for vibrationg
systems with velocity measurements and piezo actuators. Thus, the structure of the model is directly
embedded in the identification procedure, resulting into a gray-box approach to the model definition.
By using this methodology, the optimal sensors and actuator placement has been defined, by solving an
optimization problem taking into account the controllability index. Next, a broadband control law has been
derived, in order to reject broadband disturbances, as shown also by experimental results.
Next, an optimal control problem has been addressed, minimizing an H-infinity index, that is very appropriate
for noise and vibration reduction, both for its ability in structural resonance reduction and for its robustness.
However, the high dimensionality of the modeled structure, as discussed above, prevents the designer form
the use of numerical solutions of the coupled Riccati equations needed for the design of the classic H-inf
controller. Thus, a mathematically closed-form solution to the problem has been derived, suited to the
structure of the model produced by the gray-box approach, with the further properties of band-pass
frequency shape, so as to reduce high frequency amplification, leading to possible spillover effects, and low
frequency amplification, harmful if accelerometers are used, as is often the case in aeronautical applications.
Moreover, the stabilizing controller is also guaranteed to be stable, that is a crucial requisite to avoid direct
sensitivity function increase.
Moreover, the problem the definition of the scaling matrices of the modern approaches (H-2, H-inf) has also
been discussed, proposing a solution based on system specs rather than on properties of the measured
signals, due to the definition of an innovative quality index.
Recently, the case of weighting sensor signals has been faced by resorting to an LMI approach to design a
controller with more sensors than actuators (that matches the aeronautical current practice) paving the way
to the design of stable stabilizing optimal controllers with uncolocated sensor/actuator pairs.

The activities related to this topic resulted into an international monograph published by Springer.

Hydraulic Engineering Control
The problem of water flow regulation has been considered. For an artificial reservoir with a dam, fuzzy
decision and control strategies have been proposed for facing the problem of water release by suitably
operating the dam gate. Considering a desired water release profile varying during the months of the year,
the error variable, i.e. the difference between the desired and the actually released water flow is computed.
Based on the error variable, a control action is decided by a nonlinear fuzzy controller. The nonlinearity of
the controller is due to the fact that different sign of error requires qualitatively different responses, since
they are related to water shortage and water surplus. Thus, a fuzzy PID is designed, with control gains
depending nonlinearly on the error.
The desired water profile is in turn computed by using a decision strategy taking into account the current
season of the year, the mean desired water demand and the water available at the past month. An
optimization problem has been solved by using genetic algorithms, and the solution has been compared with
current state-of-the-art water release strategies. The proposed solution results in a set of fuzzy rules with
the twofold benefit of being easily interpretable by human operators and to improve the optimization
process, since a sensible starting guess can be suggested to the optimization algorithm.
Further development of this strategy have been to model the reservoir as an hybrid process (time
driven/event driven), defining the decision strategy as a supervisor for this process. Different solutions have
been compared, by using a simulator based on MATLAB-Simulink-State flow and, modeling the water inflow
time histories with AR and ARMAX models, performing Montecarlo simulations to assess the effectiveness of
the proposed approach.
The above results have been published in different international conference proceedings, journals and are
summarized in an international edited book, published by Springer.

Modelling, control and supervision for aircraft onboard systems

Modelling and simulation of complex power systems onboard large commercial aircraft (e.g., the Airbus A380
family) have been considered. The objective of the “more electric aircraft” is to reduce the number of bulky
and heavy hydraulic actuator, to be replaced by electric actuators in order to reduce weights, fuel
consumption and to increase reliability. In this activity, Alberto Cavallo has been scientific responsible for the
Research Unit of the Seconda Università di Napoli in the MOET Project, an European project funded within
FP 6 with 70M€ and with a consortium of more than 60 industrial, academic and SME partner from 18
European Countries. The activities in this project have produced two working prototypes of DC-DC converters
and two international patents.

Next, multiphysic modeling of onboard devices has been considered, with the target of producing models in
the Modelica/Dymola software environment. Since most of the devices produced by European
manufacturers for the aeronautic field was in Saber (for instance, in the above MOET project, Saber had been
used as the standard language for electric device modeling, and manufactures had to produce electric devices
along with software code in Saber of their behavioral and functional model), a preliminary step has been the
design of an automatic conversion software from Saber to Modelica. This has been the object of the SMART
project (see list of projects), within the Clean Sky initiative of the FP7. In this project, Alberto Cavallo is the
local scientific responsible.

The next step has been to obtain a complete model in Modelica of the electric network, and the design of a
controller/supervisor has been carried out by resorting to the Petri Net formalism. The task of the controller

is to handle critical situations (e.g., overloads), and the activity is developed within the ongoing SUPREMAE
project, again in Clean Sky. Further development of these studies are the development of an (Electric Power
Center), in order to build a testbench for the optimized management of electric loads, employing also new
power devices (as the SSPC, Solid State Power Controller). This activity is the object of the I-PRIMES project,
started in June 2012 and funded by FP7. Finally, two further projects on the same topics (MASDENADA and
EPOCAL) funded by Clean Sky have just reached the negotiation phase and the kick-off is scheduled by 2012.
In the latter four projects, Alberto Cavallo serves as Project Coordinator.

Automatic interpretation of human hand motion
This activity has started from the topics dealt with by the FP7 Dexmart project, leaded by Prof. Siciliano from
Università degli Studi di Napoli “Federico II”, with Seconda Università di Napoli as a partner.
The availability of robotic hands resembling more and more human hands (in terms of size, morphology,
degrees of freedom) has caused a renewed interest in the possibility of reproducing on the robot complex
movements of a dexterous human hand. This requires first the analysis and the understanding of complex
actions, that cannot be obtained by using simple heuristic approaches.
For this reason, the use of an instrumented glove (Cyberglove) is crucial for collecting signals from the human
hand. Also infrared cameras on gloves equipped with markers can be used in order to obtain kinetostatic
data, while tactile sensors embedded in the glove can be exploited in order to compute contact forces the
hand exert on the objects to manipulate.
Whatever the sensed data, sensor fusion strategies have to be used to obtain a coherent set of data. Next,
by using the properties of the singular value decomposition, a rigorous and completely automatic approach
to the problem of human hand motion understanding has been proposed. The approach is based on the
decomposition of the motion of human hand and fingers in “elementary actions” or “motion primitives”, that
can be used as “building blocks” for segmenting or reconstructing the human hand activity. Moreover, the
proposed strategy is optimized from the computational point of view, so that is can be used in real time even
when the number of signal to process is high, due to the many sensors mentioned above. The possibility to
operate in real time opens interesting developments in the improved interaction human-robot, since the
robot can be aware of what the human is currently performing.

Analysis of time histories in medical applications
Data mining strategies based on decision trees and statistical methods have been applied in the prediction
of the most frequent second tumor after a first malignancy, along with the determination of the inter-arrival
time between the two tumors.
Indeed, the improved medical and surgical techniques have sensibly increased the success rate in the
treatment of a first tumor. However, this implies an increased risk to being hit by a second, new tumor.
However, patients undergoing a first malignancy are subject to an improved follow-up, thus a large mass of
data is available to the analyst to detect a possible cause-effect relationship (an input-output model, from
the perspective of automatic control).
The essential element is the availability of a very large database (SEER) collecting more than 30 years of data
on multiple tumors in the US. By using randomized approaches the prediction of the most probable second
tumor based on preliminary features (sex, age, first tumor site, staging, histology code) has been computed
for different first tumors.
Moreover, the fuzzy model of the time-varying probability of a second tumor after a given first malignancy,
as a function of patient age and time from the diagnosis of the first tumor, has been deduced. The results of
this study have been presented in different conferences, both in National context (e.g., in the plenary lecture
of the Biannual Congress of the Italian Surgery Society, Rome, 2008) and international in the bioinfomatic

conferences (Bethesda, Washington DC), and have also appeared in a chapter of an international monograph
on Multiple Primary Malignancies, published by Springer.

Identification by using data mining strategies
The activities described in this section are the result of a collaboration with the most important industries of
the geographic area. As such the results are appeared only on internal, reserved reports (whose title is shown
at the end of this curriculum). For this reason, only a brief description of the activities is reported here.
Within a series of collaborations with the former ELASIS S.C.p.A. (Sistema di Ricerca FIAT nel Mezzogiorno,
FIAT research system in South Italy), now Fiat Group Automobile (FGA), fuzzy models have been set up to
estimate and explain faulty data, initially by using neuro-fuzzy identification (ANFIS), then by using more
sophisticated techniques, prefiltering data with orthogonal weighted least squares, removing outliers, then
using Rough Set data analysis in order to initialize a set of reasonable rules, that are then fine-tuned by using
optimization and identification techniques. The models thus obtained have shown prediction capabilities of
faulty vehicles superior to neural newtwork-based model used before by ELASIS, even when different vehicle
functional areas are considered.
Again by using data mining techniques, specifically decision trees, fault detection and fault diagnosis
problems have been tackled for the former Alania Aeronautica (now Alenia Aermacchi). A Permanent Magnet
Synchronous Motor (PMSM) has been modeled in detail, and faults have been considered in the model (both
sudden fault and time varying parameters). Then different combinations of faults have been considered, and
different simulations performed to collect different faulty data. A hierarchic approach has been used, by first
considering a partition among different load torques, then a detailed analysis that, after detection of the type
of fault (e.g., fault in bearings, in stator resistance, in a diode in the rectifier), is also able to estimate the
entity of the fault, thus diagnosing the fault.

Research Projects

    2016-2019: Principal investigator of the Project “ENIGMA” funded by the European Community under
     the initiative CleanSky2 of the Horizon2020 (Horizon2020 Programme).
    2015-2018: Principal investigator of the Project “ESTEEM” funded by the European Community under
     the initiative CleanSky2 of the Horizon2020 (Horizon2020 Programme).
    2012-2014: Alberto Cavallo is the Coordinator of the biennial project “I-PRIMES: an Intelligent Power
     Regulation using Innovative Modules for Energy Supervision” funded by the European Community under
     the initiative Clean Sky of the FP7 (7th European Framework Programme).
    Within 2012 the projects “EPOCAL: an Electrical POwer Center for Aeronautical Loads” and “MAS DE
     NADA: Modeling and Advanced Software Development for Electrical Networks in Aeronautical Domain
     Analysis” both funded on the Clean Sky initiative, will start. In both he serves as Coordinator .
    Since June 2011 he is the Coordinator of the Clean Sky project “SUPREMAE: a SUpervised Power
     Regulation for Energy Management of Aeronautical Equipments”.
    Since April 2011 he is Principal Investigator for the national triennial project PON “IESWECAN:
     Informatics for Embedded SoftWare Engineering of Construction and Agricultural machines”, leaded by
     Fiat Group Automobile.
    Since September 2010 he is Principal Investigator for the Clean Sky project SMART (Saber Model
     Automatic tRanslation Tool, a software for Saber models conversion to multi-systems simulation
     platforms).

   From 2008 to 2011 he partecipates to the European project DEXMART (DEXterous and autonomous
    dual-arm/hand robotic manipulation with sMART sensory-motor skills: A bridge from natural to artificial
    cognition), IP under the FP7, duration 4 years, where he is responsible for sensory data fusion by using
    soft computing techniques for automatic motion recognition in the operative unit of the Seconda
    Università di Napoli.
   In 2008 he participates to the Legge 5 project of the Regione Campania “Protezione Sismica di Edifici
    Esistenti mediante Tecniche di Controllo Semiattivo” (Semiactive control techniques for earthquake
    protection of buildings).
   2007. Scientific coordinator for the Dipartimento di Ingegneria dell'Informazione della Seconda
    Università di Napoli for the research project “Analisi e Progettazione di Tecniche di Controllo Sensorless
    per Motori Sincroni a Magneti Permanenti per Applicazioni Automotive”, funded by ST Microelectronics.
   2007. Scientific coordinator for the Dipartimento di Ingegneria dell'Informazione della Seconda
    Università di Napoli for the research project “Tecniche avanzate di Fault Detection e Fault Diagnosis.
    Prognosi dei guasti applicate al sistema di generazione elettrica” funded by Alenia Aeronautica, within
    the activities related to the TATEM European Research project.
   From 2006 until 2009 he participates to the Regional Center for Information Communication Technology
    (CeRICT scrl), derived from the Centro Regionale di Competenza sull’ICT (CRdC ICT).
   2007. Scientific coordinator for the Dipartimento di Ingegneria dell'Informazione della Seconda
    Università di Napoli for the research project "Tecniche di Predizione Guasti applicate al Sistema di
    Generazione e Distribuzione Elettrica” funded by Alenia Aeronautica, within the activities related to the
    TATEM European Research project.
   2006 to 2009: local coordinator for the European FP6 IP MOET (More Open Electric Aircraft), triennial
    project (6 months extension), funded with 70 M€, 62 European partners, Airbus, Eurocopter
    Deutschland GmbH, Dessault and Alenia as end user.
   Member of the Steering Committe of the above MOET project.
   In 2005 he is Principal Investigator of the Seconda Università di Napoli research unit for the biennial
    National project PRIN "Modellistica e controllo di dispositivi innovativi basati su materiali a
    magnetostrizione gigante" (modelling and control of innovative devices based on giant magnetostriction
    materials).
   In 2004 he is one of the 6 members (the only member for the Information Engineering area) of the
    Directive Board of the Centro Interdipartimentale di Ricerca in Ingegneria Ambientale (C.I.R.I.AM.)
    (interdepartmental research center for environmental engineering) of the Seconda Università di Napoli.
   He is a participant to the MESEMA (Magnetoelastic Energy Systems for Even More electric Aircraft)
    project of the FP6, with 18 European partners (SAAB Ericsson, ZF Luftfahart, Eurocopter Deutschland
    GmbH and Alenia as users). In this project he is workpackage leader for the WP “Noise and Vibration
    Control”, with two tasks "Noise and Vibration Control on turbofan aircraft" and "Noise and Vibration
    Control on helicopters", and is the largest WP of the whole project (2004-2007).
   2004. Scientific Responsible for the research project "Sviluppo di un sistema prototipale, di seguito ACC
    (Adaptive Cruise Control), funded by ELASIS S.C.p.A. (now Fiat Group Automobile).
   2004. Scientific Responsible for the research project "Caratterizzazione e certificazione affidabilistica di
    sistemi e componenti auto motive complessi”, funded by ELASIS S.C.p.A.
   2003. Scientific Responsible for the research project "Impiego della Fuzzy Logic per la previsione della
    difettosità media a diverse anzianità d’uso utilizzando sia i dati disponibili provenienti dalla banca dati,
    sia i giudizi soggettivi da parte delle funzioni aziendali coinvolte nello sviluppo di una nuova vettura”

Previsione dei dati dei difettosità di componenti e/o sistemi di un'autovettura utilizzando modelli basati
    su tecniche di soft computing" funded by ELASIS S.C.p.A.
   2002. Participant to the research project "Utilizzo della Logica Fuzzy per il miglioramento delle
    performance dei Modelli Neurali impiegati per la previsione dei dati dei difettosità di componenti e/o
    sistemi di un'autovettura" funded by ELASIS S.C.p.A.
   Participant to the national research project PRIN sul on the control of high-speed trains, 2001.
   Participant to the European FP5 research project MESA (Magnetostrictive Equipment and Systems for
    more electric Aircraft), with 12 European partners (SAAB Ericsson, ZF Luftfahart and Alenia as end users).
    Within this project he is workpackage leader for the WP “Control and Power Algorithms and Hardware”
    (2000-2003).
   Responsabile scientifico di un Progetto di Ricerca dal titolo “Procedure e metodi di controllo di processo
    e di prodotto”, dell’Università del Sannio (2000), nella mito della quale è stato responsabile nel 2000 di
    un Assegno di Ricerca triennale, successivamente rinnovato.
   Responsabile scientifico per il progetto di Ateneo “Controllo Attivo di Vibrazioni in Strutture Flessibili”
    dell’Università degli Studi del Sannio, 2000.
   Responsabile scientifico della Facoltà di Ingegneria dell’Università degli Studi del Sannio per i due
    progetti:
   Progetto pilota IFTS 1999/2000 “Esperto di PLC per l’Automazione Industriale”, di cui è stato anche
    presidente del CTS.
   Progetto pilota IFTS 1999/2000 “Progettisti software in ambiente UNIX/C/Oracle”.
   Responsabile scientifico per il progetto di Ateneo “Modellistica e Ingegneria del Controllo per i Mezzi di
    Trasporto” dell’Università degli Studi del Sannio, 1999.
   Progetto interuniversità MURST LINK, Workpackage P7 “Percorsi di formazione per profili tecnico-
    professionali con oggetto l’uso di nuove tecnologie dell’informazione e dell’automatica nelle piccole e
    medie imprese e nella pubblica amministrazione”, di cui è responsabile scientifico per il settore
    Automatica (1998).
   Partecipa al progetto Legge 41 del Dipartimento di Ingegneria Civile (sezione Idraulica) della Seconda
    Università degli Studi di Napoli sulla salvaguardia delle coste (1997).
   Partecipa al progetto P.O.P. (Progetto Operativo Plurifondo) della regione Campania, “Controllo Attivo
    del Rumore Acustico”, Misura 5.4.2., Annualità 1997.
   Partecipa al progetto PRIN “Ingegneria del Controllo”, 1997.
   Partecipa al progetto ASI “Guida e Controllo di Veicoli Orbitanti nelle fasi di Rendez-vous e Docking”,
    con la partecipazione dell’Università di Napoli “Federico II”, della Seconda Università di Napoli e del
    C.I.R.A.
   Partecipa al progetto Speciale CNR sul Controllo Robusto e Adattativo (1993).

Publications

Books
[B1] A. Cavallo, R. Setola, F. Vasca, “Guida Operativa a MATLAB, SIMULINK e Control Toolbox”, Liguori Editore,
Napoli, Italy, 1994.
[B2] A. Cavallo, R. Setola, F. Vasca, “Using MATLAB, SIMULINK and Control System Toolbox. A Practical
Approach”, Prentice Hall, London, UK, 1996.

[B3] A. Cavallo, R. Setola, F. Vasca, “La Nuova Guida a MATLAB, SIMULINK e Control Toolbox”, Liguori Editore,
Napoli, Italy, 2002.
[B4] A. Cavallo, G. De Maria, C. Natale, S. Pirozzi, “Active Control of Flexible Structures – From modelling to
implementation”, Springer-Verlag London, to appear August 2010.

International Journal Papers
[J1] A. Cavallo, G. Celentano, G. De Maria, “Robust Stability Analysis with Linearly dependent Coefficient
Perturbations”, IEEE Trans. on Automatic Control, Vol. 36, No. 3, 1991.
[J2] A. Cavallo, G. De Maria, L. Verde, “Robust Flight Control System: a Parameter Space Design”, AIAA Journal
of Guidance, Control and Dynamics, Vol. 15, No. 5, 1992.
[J3] A. Cavallo, G. De Maria, P. Nistri, “Some control problems solved via a sliding manifold approach”,
Differential Equations and Dynamical Systems, Vol. 1, No. 4, 1993.
[J4] A. Cavallo, G. De Maria, “Algorithm for Symultaneous Stabilization of a collection of Single-Input Plants”,
Int. Jour. on System Science, Vol. 20, No. 3, 1994.
[J5] A. Cavallo, F. Ferrara, “Atmospheric Reentry Control for Low Lift/Drag Vehicles”, AIAA Journal of
Guidance, Control and Dynamics, Vol. 19, No. 1, 1996.
[J6] A. Cavallo, G. De Maria, F. Ferrara, “Attitude Control for Low Lift/Drag Reentry Vehicles”, AIAA Journal of
Guidance, Control and Dynamics, Vol. 19, No. 4, 1996.
[J7] A. Cavallo, G. De Maria, P. Nistri, “A Sliding Manifold Approach to the Feedback Control of Rigid Robots”,
Int. Jour. of Robust and Nonlinear Control, Vol. 6, 1996.
[J8] A. Cavallo, L. Villani, “Sliding Manifold Approach to the control of Rigid Robot: Experimental Results”,
Control Engineering Practice, Vol. 5, No. 5, 1997.
[J9] A. Cavallo, G. De Maria, P. Nistri, “Robust Control Design with Integral Action and Limited Rate Control”,
IEEE Trans. On Automatic Control, Vol. 44, No. 8, 1999.
[J10] A. Cavallo, G. De Maria, R. Setola, “A Sliding Manifold Approach for the Vibration Reduction of Flexible
Systems”, Automatica, Vol. 35, 1999.
[J11] A. Cavallo, P. Nistri, E. Zoli, “A Second Order Sliding Control Approach for Vibration Reduction”,
Differential Equations and Dynamical Systems, Vol. 8, Nos 3/4, Jul/Oct. 2000.
[J12] A. Cavallo, C. Natale, “Output Feedback Control based on a High Order Sliding Manifold Approach”, IEEE
Trans. On Automatic Control, Vol. 48, No. 3, 2003.
[J13] A. Cavallo, C. Natale, S. Pirozzi, C. Visone, “Effects of Hysteresis Compensation in Feedback Control
Systems”, IEEE Transaction on Magnetics, Vol 39, No. 3, 2003.
[J14] A. Cavallo, A. Di Nardo, M. Di Natale, “Fuzzy Control of Artificial Reservoirs”, WSEAS Transactions on
Systems, Vol. 2, No. 4, 2003.
[J15] A. Cavallo, C. Natale, S. Pirozzi, C. Visone, “Feedback Control Systems for Micro-positioning Tasks with
Hysteresis Compensation”, IEEE Transactions on Magnetics, vol. 40, March 2004.
[J16] A. Cavallo, C. Natale, “High-Order Sliding Control of Mechanical Systems: Theory and Experiments”,
Control Engineering Practice, vol. 12, no. 9, pp. 1139-1149, Sep. 2004.

[J17] A. Cavallo, C. Natale, S. Pirozzi, C. Visone, “Limit Cycles in Control Systems Employing Smart Actuators
with Hysteresis”, IEEE/ASME Trans. on Mechatronics,April 2005.
[J18] A. Cavallo, “High Order Fuzzy Sliding Manifold Control”, Fuzzy Sets and Systems, Vol. 156, no. 2 , pp.
249-266, 2005.
[J19] A. Cavallo, G. De Maria, C. Natale, S. Pirozzi, “Gray-box Identification of Continuous-time Models of
Flexible Structures”, IEEE Control System Technologies, vol. 15, pp. 967-981, 2007.
[J20] A. Cavallo, G. De Maria, C. Natale, S. Pirozzi, “Robust Control of Flexible Structures with Stable Bandpass
Controllers”, Automatica, vol. 44, pp.1251-1260, 2008.
[J21] A. Cavallo, D. Davino, G. De Maria, C. Natale, S. Pirozzi, C. Visone, “Hysteresis compensation of smart
actuators under variable stress conditions”, Physica B- Condensed Matter, vol 403, no. 2-3, pp. 261-265, 2008.
[J22] CAVALLO A., DE MARIA G., NATALE C., PIROZZI S. (2009). Optoelectronic joint angular sensor for robotic
fingers.. SENSORS AND ACTUATORS. A, PHYSICAL, vol. 152, p. 203-210, ISSN: 0924-4247
[J23] CAVALLO A., MAY C., MINARDO A., NATALE C., PAGLIARULO P., PIROZZI S. (2009). Active vibration
control by a smart auxiliary mass damper equipped with a fiber Bragg grating sensor. SENSORS AND
ACTUATORS. A, PHYSICAL, vol. 153 n.2, p. 180-186, ISSN: 0924-4247, doi: 10.1016/j.sna.2009.05.016
[J24] Cavallo A, De Maria G, Natale C, Pirozzi S (2012). Classes of Strongly Stabilizing Bandpass Controllers for
Flexible Structures. ADVANCES IN ACOUSTICS AND VIBRATION, vol. 2012, 249478, ISSN: 1687-6261, doi:
10.1155/2012/249478
[J25] Cavallo A, Di Nardo A, De Maria G, Di Natale M (2013). Automated Fuzzy Decision and Control System
for Reservoir Management. JOURNAL OF WATER SUPPLY: RESEARCH AND TECHNOLOGY. AQUA, vol. 62, p.
189-204, ISSN: 1606-9935, doi: 10.2166/aqua.2013.046
[J26] Palli G, Melchiorri C, Vassura G, Scarcia U, Moriello L, Berselli G, Cavallo A, De Maria G, Natale C, Pirozzi
S, May C, Ficuciello F, Siciliano B (2014). The DEXMART Hand: Mechatronic Design and Experimental
Evaluation of Synergy-Based Control for Human-Like Grasping. THE INTERNATIONAL JOURNAL OF ROBOTICS
RESEARCH, vol. 33, p. 799-824, ISSN: 0278-3649, doi: 10.1177/0278364913519897
[J27] Cavallo A, De Maria G, Natale C, Pirozzi S (2014). Slipping detection and avoidance based on Kalman
filter. MECHATRONICS, vol. 24, p. 489-499, ISSN: 0957-4158, doi: 10.1016/j.mechatronics.2014.05.006
[J28] DI NARDO, Armando, CAVALLO, Alberto, DI NATALE, Michele, GRECO, Roberto, Santonastaso, Giovanni
Francesco (2016). Dynamic control of water distribution system based on network partitioning. PROCEDIA
ENGINEERING, vol. 154, p. 1275-1282, ISSN: 1877-7058, doi: 10.1016/j.proeng.2016.07.460
[J29] Cavallo A, Falco P (2014). Online Segmentation and Classification of Manipulation Actions From the
Observation of Kinetostatic Data. IEEE TRANSACTIONS ON HUMAN-MACHINE SYSTEMS, p. 1-14, ISSN: 2168-
2291, doi: 10.1109/TSMC.2013.2296569
[J30] Cavallo A, Guida B, Rubino L (2014). Boost Full Bridge Bidirectional DC/DC Converter for Supervised
Aeronautical Applications. INTERNATIONAL JOURNAL OF AEROSPACE ENGINEERING, ISSN: 1687-5966
[J31] Cavallo A., Canciello G. (2016). Selective modal control for vibration reduction in flexible structures.
AUTOMATICA,            vol.        75,         p.      282-287,          ISSN:       0005-1098,           doi:
http://dx.doi.org/10.1016/j.automatica.2016.09.043

[J32] Cavallo Alberto, Canciello Giacomo, Guida Beniamino (2017). Supervisory control of DC-DC bidirectional
converter for advanced aeronautic applications. INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR
CONTROL, ISSN: 1049-8923, doi: 10.1002/rnc.3851
[J33] Cavallo Alberto, Canciello Giacomo, Guida Beniamino (2017). Supervised control of buck-boost
converters for aeronautical applications. AUTOMATICA, vol. 83, p. 73-80, ISSN: 0005-1098, doi:
10.1016/j.automatica.2017.05.005
[J34] Canciello Giacomo, Cavallo Alberto, Guida Beniamino (2017). Robust control of aeronautical electrical
generators for energy management applications. INTERNATIONAL JOURNAL OF AEROSPACE ENGINEERING,
vol. 2017, p. 1-12, ISSN: 1687-5966, doi: 10.1155/2017/1745154
[J35] Cavallo A., Canciello G., Guida B. (2017). Energy Storage System Control for Energy Management in
Advanced Aeronautic Applications. MATHEMATICAL PROBLEMS IN ENGINEERING, vol. 2017, p. 1-9, ISSN:
1024-123X, doi: 10.1155/2017/4083132
[J36] Canciello, G., CAVALLO, Alberto, Guida, B. (2017). Control of Energy Storage Systems for Aeronautic
Applications. JOURNAL OF CONTROL SCIENCE AND ENGINEERING, vol. 2017, p. 1-9, ISSN: 1687-5249, doi:
10.1155/2017/2458590

International Book Chapters
[BC1] A. Cavallo, G. De Maria, L. Verde, “Robust Parameter Design of Flight Control Systems”, in R. Whalley
(Ed.), Application of Multivariable System Techniques, Elsevier Applied Science, London, UK, 1990.
[BC2] A. Cavallo, G. De Maria, L. Verde, “Robustness against Aerodynamic Parameter Uncertainties in Flight
Control Systems”, in P. Borne, G. Tzafestas, N.E. Radhy (Eds.) Mathematics of the Analysis and Design of
Process Control, Elsevier Science Publishers, 1992, IMACS.
[BC3] A. Cavallo, G. De Maria, “Reentry Control for Low L/D Vehicles”, in S. Sivasundaram (Ed.), Nonlinear
Problems in Aeronautics and Astronautics, Gordon and Breach Science Publisher, USA, 1998.
[BC4] A. Cavallo, G. De Maria, C. Natale, “High Order Sliding Manifold Control for Vibration Reduction in
Flexible Structures”, in J. Allan, R.J. Hill, C.A. Brebbia, G. Sciutto and S. Sone (Eds.) Computers in Railways VIII,
WIT Press, UK, 2002.
[BC5] A. Cavallo, A. Di Nardo, M. Di Natale, “A Fuzzy Control Strategy for the Regulation of an Artificial
Reservoir”, in E. Beriatos, C.A. Brebbia, H. Coccossis and A. Kungolos (Eds.) Sustainable Planning and
Development, WIT Press, UK, 2003.
[BC6] A. Cavallo, A. Di Nardo, “Optimal Fuzzy Management of Reservoir based on Genetic Algorithms”, in R.
Lowen and A. Verschoren (Eds.) Foundations of Generic Optimization volume 2: Applications of Fuzzy Control,
Genetic Algorithms and Neural Networks., Springer-Verlag, 2007, ISBN: 978-1-4020-6667-2.
[BC7] A. Cavallo, C. Dodaro, “Bioinformatics in MPM: Prediction of a Second Tumor Site by using Decision
Trees”, in A. Renda (Ed.) Multiple Primary Malignancies, Springer-Verlag, 2008, ISBN: 978-88-470-1094-9.

International Conference Papers
[C1] A. Cavallo, G. Celentano, G. De Maria, “Robust Stability Analysis of Uncertain Linear Time Invariant
Dynamical Systems”, Proc. of 28th IEEE Conference on Decision and Control, December 1989, Tampa (USA).
[C2] A. Cavallo, G. De Maria, L. Verde, “Parameter Space Design of Robust Flight Control Systems”, 50th
Symposium of the Guidance and Control Panel AGARD, May 1990, Cesme, Turkey.

[C3] A. Cavallo, G. De Maria, L. Verde, “Robust Analysis of handling qualities in Aerospace Systems”, Proc. of
the 11th World Congress of the IFAC, August 1990, Tallin, Estonia.
[C4] A. Cavallo, G. Celentano, G. De Maria, “Robust Controller Design of Uncertain Linear Time Invariant SISO
Plants”, Proc. of the 11th World Congress of the IFAC, August 1990, Tallin, Estonia.
[C5] A. Cavallo, G. De Maria, L. Verde, “Sensitivity Minimization with Pole Assignment in SISO Systems”, Proc.
of the 29th IEEE Conference on Decision and Control, December 1990, Honolulu, Hawaii, USA.
[C6] A. Cavallo, G. De Maria, “A Polynomial Approach to Simultaneous Stabilization of SISO Plants”, Proc. of
the 30th IEEE Conference on Decision and Control, December 1991, Brighton, UK.
[C7] A. Cavallo, G. De Maria, P. Marino, “Simulation Model for Cathalytic Monopropellant Hydrazine
Thrusters”, Proc. of the IFAC Syposium on Intelligent Components and Instruments for Control Applications
SICICA'92, May 1992, Malaga, Spain.
[C8] A. Cavallo, G. De Maria, V. De Nicola, F. Ferrara, “A Re-entry Capsule Control System Design for
Microgravity Experiments”, Proc. del 12th IFAC Symposium on Automatic Control in Aerospace, September
1992, Ottobrunn, Germany.
[C9] A. Cavallo, G. De Maria, “A Note on Computing the Minimum Distance between Lyapunov Functions”,
Proc. of the 31st IEEE Conference on Decision and Control, 16-18 December 1992, Tucson (USA).
[C10] A. Cavallo, G. De Maria, P. Nistri, “Nonlinear Tracking Problems by a Sliding Manifold Approach”, Proc.
of the IEEE Mediterranean Symp. on New Directions in Control Theory and Applications, June 1993, Creta,
Greece.
[C11] A. Cavallo, G. De Maria, P. Nistri, “Linear Tracking Problems by a Sliding Manifold Approach”, Proc. of
the 2nd European Control Conference, 28 Giugno-1 Luglio 1993, Groningen, The Netherlands.
[C12] A. Cavallo, G. De Maria, F. Ferrara, P. Nistri, “A Sliding Manifold Approach to Satellite Attitude Control”,
Proc. of the 12th IFAC World Congress, July 1993, Sydney, Australia.
[C13] A. Cavallo, G. De Maria, P. Marino, F. Vasca, “Pulse Ratio Modulator Design via Sliding Mode Approach”,
Proc. of the IEEE Symposium on Industrial Electronics, May 1994, Santiago, Chile.
[C14] A. Cavallo, G. De Maria, P. Nistri, “Robust LQ Design by a Sliding Manifold Approach”, IFAC Workshop
on New Trends in Design of Control Systems, September 1994, Smolenice, Slovenia.
[C15] A. Cavallo, F. Vasca, “DC Motor Control with Sliding Mode Switching Modulators”, Proc. of the 20th IEEE
Conference on Industrial Electronics, Control and Instrumentation, September 1994, Bologna, Italy.
[C16] A. Cavallo, G. De Maria, P. Nistri, “Sliding Mode Techniques with Robust Observers”, IEEE Workshop on
Robust Control via Variable Structure & Lyapunov Techniques VSLT94, September 1994, Benevento, Italy.
[C17] A. Cavallo, G. De Maria, F. Ferrara, E. Filippone, “A Trajectory and Attitude Control Strategy for the
CRV/CTV Atmospheric Re-entry”, Paper No. AIAA 96-3703, AIAA Guidance, Navigation and Control
Conference, July 1996, San Diego (USA).
[C18] A. Cavallo, G. De Maria, “Attitude Control for Large Angle Maneuvers”, IEEE International Workshop on
Variable Structure Systems VSS96, December 1996, Tokio (Japan).
[C19] A. Cavallo, G. De Maria, “Limited Rate Control with a Singular Perturbation Approach”, 4th European
Control Conference ECC97, June 1997, Brussel (Belgium).

[C20] A. Cavallo, G. De Maria, R. Setola, “Sliding Manifold Approach to Vibration Control of Flexible Systems
subject to Narrow-Band Disturbances”, 4th European Control Conference ECC97, June 1997, Brussel
(Belgium).
[C21] A. Cavallo, G. De Maria, R. Setola, “Vibration Control of Flexible Systems Via Sliding Manifold Approach”,
2nd IFAC Symposium of Robust Control Design, ROCOND 97, June 1997, Budapest (Hungary).
[C22] A. Cavallo, E. Leccia, “Fuzzy Control of Rigid Robots Via a Sliding Manifold Approach”, Proc. of the 5th
European Congress on Intelligent Techniques and Soft Computing, EUFIT 97, September 1997, Aachen,
Germany.
[C23] A. Cavallo, G. De Maria, E. Leccia, R. Setola, “A Robust Controller for Active Vibration Control of Flexible
Systems”, Proc. of the 36th IEEE Conference on Decision and Control, Dicembre 1997, San Diego (USA).
[C24] A. Cavallo, E. Leccia, R. Setola, “Experimental Results on a Second Order Sliding Manifold Approach for
Tracking Problems”, Proc. of the 1998 IEEE Conference on Control Applications, September 1998, Trieste,
Italy.
[C25] A. Cavallo, F. Garofalo, F. Vasca, G. Zitano, “State Feedback Fuzzy Control for Pulse Width Modulated
Systems”, Proc. of the 6th European Congress on Intelligent Techniques and Soft Computing, EUFIT 98,
September 1998, Aachen (Germany).
[C26] A. Cavallo, G. De Maria, E. Leccia, R. Setola, “Robust Control of a DC9 Aircraft Frame”, Proc. of the 37th
IEEE Conference on Decision and Control, Dicembre 1998, Tampa (USA).
[C27] A. Cavallo, G. De Maria, “Robust Active Control of Flexible Systems with Second Order Sliding”, Proc. of
the 1999 IEEE/ASME Conference on Advanced Intelligent Mechatronics, settembre 1999, Atlanta (USA).
[C28] A. Cavallo, G. De Maria, C. Natale, “Second Order Sliding Manifold Approach for Vibration Reduction
via Output Feedback: Experimental Results”, IEEE/ASME International Conference on Advanced Intelligent
Mechatronics, pp. 725-730, Como, I, 2001
[C29] A. Cavallo, C. Natale, C.Visone, “Compensation of Hysteretic Effects in Feedback Control Systems”, The
10th Biennial IEEE Conference on Electromagnetic Field Computation Perugia, Italy, June 16-19, 2002
[C30] A. Cavallo, C. Natale, “A robust output feedback control law for MIMO plants”, Proc. of the 15th IFAC
World Congress, Barcelona, Spain, July 2002.
[C31] C. Natale, F. Franco, A. Cavallo, F. Marulo “A Feedback Broadband Vibration Control of an Aeronautical
Panel”, International Symposium on Active Control of Sound and Vibration, Southampton University, UK, July
2002.
[C32] G. Aurilio, A. Cavallo, L. Lecce, E. Monaco, L. Napolitano, C. Natale, “Fuselage Frame Vibration Control
Using Magnetostrictive Hybrid Dynamic Vibration Absorbers”, 5th European Conference on Noise Control,
Napoli, Italy, May 2003.
[C33] A. Cavallo, C. Natale, P. Capasso “Robust Output Feedback Control for the Lateral Dynamics of a Railway
Car”, European Control Conference ECC03, Cambridge, UK, Sept. 2003.
[C34] A. Cavallo, C. Natale, S. Pirozzi, C. Visone, “Feedback Control Systems for Micro-positioning Tasks with
Hysteresis Compensation”, Compumag 2003.
[C35] A. Cavallo, A. Di Nardo, M. Di Natale, “Optimal Fuzzy Decision Strategies for Reservoir Management”,
ASCE World Water and Environmental Resources Congress, Salt Lake City, Utha, June 2004.