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Prof. Alessandro Casavola
Department of Informatics, Modeling, Electronics and System Engineering, University of Calabria, Rende, Italy

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Research Keywords & Expertise

0 Control Engineering
0 Vehicle Dynamics and Control
0 fault diagnosis and fault-tolerant control
0 Distributed control and optimization
0 Decentralized Control

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fault diagnosis and fault-tolerant control
Decentralized Control

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Journal article
Published: 28 June 2021 in International Journal of Control
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This paper presents some outcomes of a recently completed research project aimed at developing torque control strategies for automotive turbocharged combustion engines with modern control design methodologies. Traditional torque control consists of maintaining some relevant signals close to certain set-points generated by a map representing the static inverse model of the engine, without any consideration for the optimality of the responses. The proposed model-based control strategy does not make use of any static map and all signals of interests are regulated at the same time by a unique centralised multivariable controller. A Linear Parameter Varying (LPV) H∞ optimal control design problem, formulated via Linear Matrix Inequality (LMI) feasibility conditions, is solved to generate the controller, whose main objectives are the reduction of fuel consumption while maintaining good torque tracking. The resulting regulator presents is gain-scheduled and is designed to be calibratable in real-time. Some numerical simulations demonstrate the effectiveness of the presented approach.

ACS Style

Gianfranco Gagliardi; Francesco Tedesco; Alessandro Casavola. H∞ Calibratable LPV Control Strategies for Torque Control in Automotive Turbocharged Engines. International Journal of Control 2021, 1 -33.

AMA Style

Gianfranco Gagliardi, Francesco Tedesco, Alessandro Casavola. H∞ Calibratable LPV Control Strategies for Torque Control in Automotive Turbocharged Engines. International Journal of Control. 2021; ():1-33.

Chicago/Turabian Style

Gianfranco Gagliardi; Francesco Tedesco; Alessandro Casavola. 2021. "H∞ Calibratable LPV Control Strategies for Torque Control in Automotive Turbocharged Engines." International Journal of Control , no. : 1-33.

Journal article
Published: 13 June 2021 in Sensors
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This paper presents the design and validation of a model-based H vehicle lateral controller for autonomous vehicles in a simulation environment. The controller was designed so that the position and orientation tracking errors are minimized and so that the vehicle is able to follow a trajectory computed in real-time by exploiting proper video-processing and lane-detection algorithms. From a computational point of view, the controller is obtained by solving a suitable LMI optimization problem and ensures that the closed-loop system is robust with respect to variations in the vehicle’s longitudinal speed. In order to show the effectiveness of the proposed control strategy, simulations have been undertaken by taking advantage of a co-simulation environment jointly developed in Matlab/Simulink © and Carsim 8 ©. The simulation activity shows that the proposed control approach allows for good control performance to be achieved.

ACS Style

Gianfranco Gagliardi; Marco Lupia; Gianni Cario; Alessandro Casavola. Optimal H Control for Lateral Dynamics of Autonomous Vehicles. Sensors 2021, 21, 4072 .

AMA Style

Gianfranco Gagliardi, Marco Lupia, Gianni Cario, Alessandro Casavola. Optimal H Control for Lateral Dynamics of Autonomous Vehicles. Sensors. 2021; 21 (12):4072.

Chicago/Turabian Style

Gianfranco Gagliardi; Marco Lupia; Gianni Cario; Alessandro Casavola. 2021. "Optimal H Control for Lateral Dynamics of Autonomous Vehicles." Sensors 21, no. 12: 4072.

Journal article
Published: 23 January 2021 in Sensors
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In underwater localization systems several sources of error may impact in different ways the accuracy of the final position estimates. Through simulations and statistical analysis it is possible to identify and characterize such sources of error and their relative importance. This is especially of use when an accurate localization system has to be designed within required accuracy prescriptions. This approach allows one to also investigate how much these sources of error influence the final position estimates achieved by an Extended Kalman Filter (EKF). This paper presents the results of experiments designed in a virtual environment used to simulate real acoustic underwater localization systems. The paper intends to analyze the main parameters that significantly influence the position estimates achieved by a Short Baseline (SBL) system. Specifically, the results of this analysis are presented for a proprietary localization system constituted by a surface platform equipped with four acoustic transducers used for the localization of an underwater target. The simulator here presented has the purpose of simulating the hardware system and modifying some of its design parameters, such as the base-line length and the errors on the GPS and Inertial Measurement Unit (IMU) units, in order to understand which parameters have to modify for improving the accuracy of the entire positioning system. It is shown that statistical analysis techniques can be of help in determining the best values of these parameters that permit to improve the performance of a real hardware system.

ACS Style

Gianni Cario; Alessandro Casavola; Gianfranco Gagliardi; Marco Lupia; Umberto Severino. Accurate Localization in Acoustic Underwater Localization Systems. Sensors 2021, 21, 762 .

AMA Style

Gianni Cario, Alessandro Casavola, Gianfranco Gagliardi, Marco Lupia, Umberto Severino. Accurate Localization in Acoustic Underwater Localization Systems. Sensors. 2021; 21 (3):762.

Chicago/Turabian Style

Gianni Cario; Alessandro Casavola; Gianfranco Gagliardi; Marco Lupia; Umberto Severino. 2021. "Accurate Localization in Acoustic Underwater Localization Systems." Sensors 21, no. 3: 762.

Journal article
Published: 20 January 2021 in IEEE Transactions on Industrial Electronics
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This paper proposes a second-order sliding mode control (SOSMC) law, based on a super twisting algorithm, aimed at regulating the output voltage of a DC-DC buck converter. A closed-loop system is designed consisting of two distinct nested loops organized within a cascaded super twisting algorithm structure. Several sliding mode control algorithms are here surveyed for the regulation of a DC-DC buck converter. The super-twisting algorithm of second order sliding mode is also experimented in a HIL system. The comparative evaluations include comparing the output voltage transient responses to load step changes for all developed sliding mode control algorithms and the start-up responses of the output voltage to step changes of the input voltage of the buck converter. Furthermore, theoretical considerations, numerical simulations and experimental results from a laboratory prototype are compared, at different operating points, for all surveyed control methods. It results from the simulations and experiments that the designed super twisting algorithm achieves the fastest convergence, a consistent chattering reduction, the smallest settling time under loaded situations and small steady-state error during load changes over all contrasted control methods.

ACS Style

Seyed Mehdi Rakhtala; Alessandro Casavola. Real Time Voltage Control based on a Cascaded Super Twisting Algorithm Structure for DC-DC Converters. IEEE Transactions on Industrial Electronics 2021, PP, 1 -1.

AMA Style

Seyed Mehdi Rakhtala, Alessandro Casavola. Real Time Voltage Control based on a Cascaded Super Twisting Algorithm Structure for DC-DC Converters. IEEE Transactions on Industrial Electronics. 2021; PP (99):1-1.

Chicago/Turabian Style

Seyed Mehdi Rakhtala; Alessandro Casavola. 2021. "Real Time Voltage Control based on a Cascaded Super Twisting Algorithm Structure for DC-DC Converters." IEEE Transactions on Industrial Electronics PP, no. 99: 1-1.

Journal article
Published: 08 December 2020 in IEEE Transactions on Automatic Control
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A novel and original distributed reputation mechanism is here proposed for a class of networked systems characterized by two distinct groups of nodes: user agents and service providers (servers/resources). The proposed methodology is in charge of intercepting those resources that have the highest Quality of Service on the basis of their reputation (trust) shared among agents. Such a reputation may change over the time mainly influenced by changing performance indexes and other events. As a result, it is shown that the trust evolution can be modeled as the output of a positive switching linear system. This model straightforwardly allows one to prove trust boundedness and other relevant steady-state properties. To illustrate the benefits of this approach, a sensors selection problem for state estimation is outlined and addressed within the proposed framework. In particular, it is formally proved that the resulting estimation scheme ensures, over the time, the selection of the sensor with the current best perceived QoS in a finite time.

ACS Style

Francesco Tedesco; Giuseppe Franze; Alessandro Casavola. A reputation mechanism for dynamical interactions in multi-agent systems under quality of service requirements. IEEE Transactions on Automatic Control 2020, PP, 1 -1.

AMA Style

Francesco Tedesco, Giuseppe Franze, Alessandro Casavola. A reputation mechanism for dynamical interactions in multi-agent systems under quality of service requirements. IEEE Transactions on Automatic Control. 2020; PP (99):1-1.

Chicago/Turabian Style

Francesco Tedesco; Giuseppe Franze; Alessandro Casavola. 2020. "A reputation mechanism for dynamical interactions in multi-agent systems under quality of service requirements." IEEE Transactions on Automatic Control PP, no. 99: 1-1.

Journal article
Published: 07 December 2020 in Smart Cities
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This paper reports the results of a recently concluded R&D project, SCALS (Smart Cities Adaptive Lighting System), which aimed at the development of all hardware/software components of an adaptive urban smart lighting architecture allowing municipalities to manage and control public street lighting lamps. The system is capable to autonomously adjust street lamps’ brightness on the basis of the presence of vehicles (busses/trucks, cars, motorcycles and bikes) and/or pedestrians in specific areas or segments of the streets/roads of interest to reduce the energy consumption. The main contribution of this work is to design a low cost smart lighting system and, at same time, to define an IoT infrastructure where each lighting pole is an element of a network that can increase their amplitude. More generally, the proposed smart infrastructure can be viewed as the basis of a wider technological architecture aimed at offering value-added services for sustainable cities. The smart architecture combines various sub-systems (local controllers, motion sensors, video-cameras, weather sensors) and electronic devices, each of them in charge of performing specific operations: remote street segments lamp management, single street lamp brightness control, video processing for vehicles motion detection and classification, wireless and wired data exchanges, power consumptions analysis and traffic evaluation. Two pilot sites have been built up in the project where the smart architecture has been tested and validated in real scenarios. Experimental results show that energy savings of up to 80% are possible compared to a traditional street lamp system.

ACS Style

Gianfranco Gagliardi; Marco Lupia; Gianni Cario; Francesco Tedesco; Francesco Cicchello Gaccio; Fabrizio Lo Scudo; Alessandro Casavola. Advanced Adaptive Street Lighting Systems for Smart Cities. Smart Cities 2020, 3, 1495 -1512.

AMA Style

Gianfranco Gagliardi, Marco Lupia, Gianni Cario, Francesco Tedesco, Francesco Cicchello Gaccio, Fabrizio Lo Scudo, Alessandro Casavola. Advanced Adaptive Street Lighting Systems for Smart Cities. Smart Cities. 2020; 3 (4):1495-1512.

Chicago/Turabian Style

Gianfranco Gagliardi; Marco Lupia; Gianni Cario; Francesco Tedesco; Francesco Cicchello Gaccio; Fabrizio Lo Scudo; Alessandro Casavola. 2020. "Advanced Adaptive Street Lighting Systems for Smart Cities." Smart Cities 3, no. 4: 1495-1512.

Journal article
Published: 04 December 2020 in Remote Sensing
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In scientific and technical diving, the survey of unknown or partially unexplored areas is a common task that requires an accurate planning for ensuring the optimal use of resources and the divers’ safety. In particular, in any kind of diving activity, it is essential to foresee the “dive profile” that represents the diver’s exposure to pressure over time, ensuring that the dive plan complies with the specific safety rules that have to be applied in accordance with the diver’s qualification and the environmental conditions. This paper presents a novel approach to dive planning based on an original underwater pathfinding algorithm that computes the best 3D path to follow during the dive in order to be able to maximise the number of points of interest (POIs) visited, while taking into account the safety limitations. The proposed approach, for the first time, considers the morphology of the 3D space in which the dive takes place to compute the best path, taking into account the decompression limits and avoiding the obstacles through the analysis of a 3D map of the site. Moreover, three different cost functions are proposed and evaluated to identify the one that could suit the divers’ needs better.

ACS Style

Marino Mangeruga; Alessandro Casavola; Francesco Pupo; Fabio Bruno. An Underwater Pathfinding Algorithm for Optimised Planning of Survey Dives. Remote Sensing 2020, 12, 3974 .

AMA Style

Marino Mangeruga, Alessandro Casavola, Francesco Pupo, Fabio Bruno. An Underwater Pathfinding Algorithm for Optimised Planning of Survey Dives. Remote Sensing. 2020; 12 (23):3974.

Chicago/Turabian Style

Marino Mangeruga; Alessandro Casavola; Francesco Pupo; Fabio Bruno. 2020. "An Underwater Pathfinding Algorithm for Optimised Planning of Survey Dives." Remote Sensing 12, no. 23: 3974.

Journal article
Published: 27 November 2020 in Control Engineering Practice
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An effective Air-to-Fuel Ratio (AFR) control is paramount to ensure a good combustion and high catalyst efficiency. This work addresses the problem of determining continuous-time estimates of AFR in turbocharged Spark Ignition (SI) engines on the basis of binary sparse measurements of the exhaust gas Oxygen. The latter are provided by a HEGO (Heated Exhaust Gas Oxygen) sensor installed at the catalytic converter input in place of a more expensive linear UEGO (Universal Exhaust Gas Oxygen) sensor, as nowadays common in commercial cars. The HEGO sensor outputs two voltage values only, corresponding respectively to low or high concentration of the residual Oxygen in the exhaust gas (on/off behavior). In view of this, it can be classified as a binary sensor generating irregular and sparse measurements in that the useful information is only present at the instants of the on/off and off/on transitions. An estimation scheme based on the use of a recursive least-squares algorithm has been designed by resorting to the theory of linear hybrid observers with quantized inputs. A detailed convergence analysis of the state reconstruction error is also provided. The proposed hybrid observer scheme is employed in a PI control-loop designed to maintain the AFR close to a desired value. The effectiveness of the proposed method is demonstrated by several numerical simulations based on both synthetic and real data.

ACS Style

Gianfranco Gagliardi; Daniele Mari; Francesco Tedesco; Alessandro Casavola. An Air-to-Fuel ratio estimation strategy for turbocharged spark-ignition engines based on sparse binary HEGO sensor measures and hybrid linear observers. Control Engineering Practice 2020, 107, 104694 .

AMA Style

Gianfranco Gagliardi, Daniele Mari, Francesco Tedesco, Alessandro Casavola. An Air-to-Fuel ratio estimation strategy for turbocharged spark-ignition engines based on sparse binary HEGO sensor measures and hybrid linear observers. Control Engineering Practice. 2020; 107 ():104694.

Chicago/Turabian Style

Gianfranco Gagliardi; Daniele Mari; Francesco Tedesco; Alessandro Casavola. 2020. "An Air-to-Fuel ratio estimation strategy for turbocharged spark-ignition engines based on sparse binary HEGO sensor measures and hybrid linear observers." Control Engineering Practice 107, no. : 104694.

Review article
Published: 25 November 2020 in Journal of Process Control
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Incipient faults almost occur gradually at a low rate in systems and usually are unnoticeable during their early stages. If diagnostic tools or proper monitoring systems ignore them, they could not be detectable until their effects become severe and cause catastrophic damages to systems. This paper presents a survey on model-based (incipient) fault diagnosis approaches to show the significance of the incipient faults diagnosis in nonlinear closed-loop systems and, by taking a glance through data-based incipient fault diagnosis advancements, a picture of their present state of the art is also briefly discussed for completeness. Moreover, a classification of the most used state estimation filters is also provided. Consequently, recent works on incipient fault diagnosis approaches are reviewed, and an incipient fault diagnosis case study is investigated for a discrete-time nonlinear open-loop system affected by stochastic noise and disturbances. Specifically, a numerical example of a closed-loop three-tank system is considered, and simulations are accomplished, to demonstrate the inability of open-loop incipient fault diagnosis approaches in detecting incipient faults in the proposed closed-loop system.

ACS Style

H. Safaeipour; M. Forouzanfar; A. Casavola. A survey and classification of incipient fault diagnosis approaches. Journal of Process Control 2020, 97, 1 -16.

AMA Style

H. Safaeipour, M. Forouzanfar, A. Casavola. A survey and classification of incipient fault diagnosis approaches. Journal of Process Control. 2020; 97 ():1-16.

Chicago/Turabian Style

H. Safaeipour; M. Forouzanfar; A. Casavola. 2020. "A survey and classification of incipient fault diagnosis approaches." Journal of Process Control 97, no. : 1-16.

Journal article
Published: 20 July 2020 in IEEE Transactions on Control Systems Technology
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Obtaining accurate measures of the turbocharger rotational speed is a key task to achieve good powertrain control performance in turbocharged combustion engines. However, direct access to the rotating parts of a turbocharger requires expensive sensors that present long-term reliability issues. In view of this, this article focuses on the design of measurement architectures for the estimation of the turbocharger shaft rotating speed via the numerical processing of the overall sound emissions acquired by a microphone placed in the vehicle hood. This kind of signal represents an extremely rich source of information about the operating conditions of all noisy powertrain subsystems. The core of the scheme is represented by an adaptive discrete-time nonlinear frequency locked-loop (FLL) filter that is properly designed to extract the useful frequency content from the acquired audio signal. The whole architecture is innovative, flexible, and extremely low cost by requiring, for its implementation, the additional installation of a single microphonic capsule only. Moreover, it exhibits such a modest computational burden to be directly implementable in commercial engine control units (ECUs) without requiring additional computing hardware. Reported experimental assessments show that the accuracy of the estimate is excellent in all allowed rotational speed regimes.

ACS Style

Gianfranco Gagliardi; Francesco Tedesco; Alessandro Casavola. An Adaptive Frequency-Locked-Loop Approach for the Turbocharger Rotational Speed Estimation via Acoustic Measurements. IEEE Transactions on Control Systems Technology 2020, 29, 1437 -1449.

AMA Style

Gianfranco Gagliardi, Francesco Tedesco, Alessandro Casavola. An Adaptive Frequency-Locked-Loop Approach for the Turbocharger Rotational Speed Estimation via Acoustic Measurements. IEEE Transactions on Control Systems Technology. 2020; 29 (4):1437-1449.

Chicago/Turabian Style

Gianfranco Gagliardi; Francesco Tedesco; Alessandro Casavola. 2020. "An Adaptive Frequency-Locked-Loop Approach for the Turbocharger Rotational Speed Estimation via Acoustic Measurements." IEEE Transactions on Control Systems Technology 29, no. 4: 1437-1449.

Journal article
Published: 22 May 2020 in Vibration
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Regenerative suspension systems, unlike traditional passive, semi-active or active setups, are able to convert the traditionally wasted kinetic energy into electricity. This paper discusses flexible multi-objective control design strategies based on LMI formulations to suitably trade-off between the usual road handling and ride comfort performance and the amount of energy to be harvested. An electromechanical regenerative vehicle suspension system is considered where the shock absorber of each wheel is replaced by a linear electrical motor which is actively governed. It is shown by simulations that multivariable centralized control laws designed on the basis of a full-car model of the suspension system are able to achieve larger amount of harvested energy under identical ride comfort prescriptions with respect to scalar decentralized control strategies, designed on the basis of a single quarter-car model and implemented independently on each wheel in a decentralized way. Improvements up to 40 % and 20 % of harvested energy are respectively achievable by the centralized multivariable H 2 and H ∞ optimal controllers under the same test conditions.

ACS Style

Alessandro Casavola; Francesco Tedesco; Pasquale Vaglica. H2 and H Optimal Control Strategies for Energy Harvesting by Regenerative Shock Absorbers in Cars. Vibration 2020, 3, 99 -115.

AMA Style

Alessandro Casavola, Francesco Tedesco, Pasquale Vaglica. H2 and H Optimal Control Strategies for Energy Harvesting by Regenerative Shock Absorbers in Cars. Vibration. 2020; 3 (2):99-115.

Chicago/Turabian Style

Alessandro Casavola; Francesco Tedesco; Pasquale Vaglica. 2020. "H2 and H Optimal Control Strategies for Energy Harvesting by Regenerative Shock Absorbers in Cars." Vibration 3, no. 2: 99-115.

Journal article
Published: 01 January 2020 in IFAC-PapersOnLine
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In this paper a supervisory strategy for load/frequency control problems in networked multi-area electrical micro-grids in the presence of Renewable Energy Systems (RES) is presented. The proposed strategy exploits a recently developed constrained supervision methodology known in the literature as the Reference-Offset Governor (ROG) approach. Here, the ROG approach is extended to operate in the presence of rate-bounded disturbances acting as non-manipulable inputs on the plant. The main aim is at adequately orchestrating, during the on-line operations, the switching among different ROG configurations, suitably calibrated on the intensity of the disturbances, to efficiently satisfy the prescribed constraints. It is shown that the use of a bank of ROGs, instead of a single one, can remarkably reduce the conservativeness of the solution and improve the overall performance if the disturbance intensity changes. The effectiveness of the proposed approach is demonstrated on a two-area power system subject to coordination constraints on maximum frequency deviations, exchanged and generated powers and injected power from local RESs.

ACS Style

Francesco Tedesco; Alessandro Casavola. Load/Frequency Control in the presence of Renewable Energy Systems: a Reference-Offset Governor approach. IFAC-PapersOnLine 2020, 53, 12548 -12553.

AMA Style

Francesco Tedesco, Alessandro Casavola. Load/Frequency Control in the presence of Renewable Energy Systems: a Reference-Offset Governor approach. IFAC-PapersOnLine. 2020; 53 (2):12548-12553.

Chicago/Turabian Style

Francesco Tedesco; Alessandro Casavola. 2020. "Load/Frequency Control in the presence of Renewable Energy Systems: a Reference-Offset Governor approach." IFAC-PapersOnLine 53, no. 2: 12548-12553.

Journal article
Published: 19 September 2019 in IFAC-PapersOnLine
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This paper deals with the estimation of the turbocharger rotating speed via the numerical processing of the overall sound emissions acquired via a microphone placed under the vehicle hood. As a matter of fact, this kind of signals represents an extremely rich information source about the operating conditions of all the noisy powertrain subsystems. The core of the scheme is represented by an adaptive Frequency Locked-Loop (FLL) filter that is properly designed so as to extract useful frequency content from the acquired audio signals. The whole architecture, requiring the use of a single microphone only, can be considered innovative and low-cost for automotive applications. Experimental outcomes demonstrate that the approach is ready to be introduced in the Engine Control Unit (ECU) in order to implement suitable strategies for turbocharger control.

ACS Style

Gianfranco Gagliardi; Francesco Tedesco; Alessandro Casavola. Turbocharger Rotational Speed Estimation via Acoustic Measurements. IFAC-PapersOnLine 2019, 52, 273 -278.

AMA Style

Gianfranco Gagliardi, Francesco Tedesco, Alessandro Casavola. Turbocharger Rotational Speed Estimation via Acoustic Measurements. IFAC-PapersOnLine. 2019; 52 (5):273-278.

Chicago/Turabian Style

Gianfranco Gagliardi; Francesco Tedesco; Alessandro Casavola. 2019. "Turbocharger Rotational Speed Estimation via Acoustic Measurements." IFAC-PapersOnLine 52, no. 5: 273-278.

Journal article
Published: 11 October 2018 in IFAC-PapersOnLine
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This paper presents a fault-tolerant sensor reconciliation design approach for over-sensed plants (see Fig. 1). The reconciliator is in charge of detecting, at each time instant, the possibly faulty physical sensors y and generating a virtual output z (with dimy ≥ dimz) where the corrupted measures coming from the pool of redundant physical output are removed. In this way the virtual output is always healthy and usable for control purposes without requiring the reconfiguration of the nominal control law. The approach is based on the use of Unknown Input Observers (UIO) with Linear Fractional Transformation (LFT) parameter dependency and works together with an "ad-hoc" parameters estimator that is designed to estimate on-line at each time instant the sensor effectiveness matrix. The sensor faults here considered are limited to variation of sensors’ gain and offset values. All main properties of the scheme are investigated and rigorously proved. A final simulation example is included to show the effectiveness of the proposed scheme.

ACS Style

Hamid Behzad; Alessandro Casavola; Francesco Tedesco; Mohammad Ali Sadrnia. Fault-Tolerant Sensor Reconciliation Schemes via LFT Unknown Input Observers. IFAC-PapersOnLine 2018, 51, 874 -879.

AMA Style

Hamid Behzad, Alessandro Casavola, Francesco Tedesco, Mohammad Ali Sadrnia. Fault-Tolerant Sensor Reconciliation Schemes via LFT Unknown Input Observers. IFAC-PapersOnLine. 2018; 51 (24):874-879.

Chicago/Turabian Style

Hamid Behzad; Alessandro Casavola; Francesco Tedesco; Mohammad Ali Sadrnia. 2018. "Fault-Tolerant Sensor Reconciliation Schemes via LFT Unknown Input Observers." IFAC-PapersOnLine 51, no. 24: 874-879.

Review article
Published: 18 July 2018 in Journal of the Franklin Institute
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This paper illustrates the derivation of a linear parameter varying (LPV) model approximation of a turbocharged Spark-Ignition (SI) automotive engine and its usage in designing a model-based fault detection and isolation (FDI) scheme. The LPV approximation is derived from a detailed nonlinear mathematical model of the engine on the basis of the well known Jacobian approach. The resulting LPV representation is then exploited for synthesizing a bank of LPV-FDI H∞/H− Luenberger observers. Each observer is in charge of detecting a particular class of fault and is designed for having low sensitivity to all other exogenous inputs so as to allow an effective fault isolation. The adopted FDI scheme is gain-scheduled and exploits a set of engine variables, assumed to be measurable on-line, as a scheduling parameters. The goodness of the LPV approximation of the engine model and the effectiveness of the LPV-FDI architecture are demonstrated by several numerical simulations.

ACS Style

Gianfranco Gagliardi; Francesco Tedesco; Alessandro Casavola. A LPV modeling of turbocharged spark-ignition automotive engine oriented to fault detection and isolation purposes. Journal of the Franklin Institute 2018, 355, 6710 -6745.

AMA Style

Gianfranco Gagliardi, Francesco Tedesco, Alessandro Casavola. A LPV modeling of turbocharged spark-ignition automotive engine oriented to fault detection and isolation purposes. Journal of the Franklin Institute. 2018; 355 (14):6710-6745.

Chicago/Turabian Style

Gianfranco Gagliardi; Francesco Tedesco; Alessandro Casavola. 2018. "A LPV modeling of turbocharged spark-ignition automotive engine oriented to fault detection and isolation purposes." Journal of the Franklin Institute 355, no. 14: 6710-6745.

Original articles
Published: 13 July 2018 in International Journal of Control
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This paper proposes two fault-tolerant sensor reconciliation design methods for over-sensed plants. The aim of the reconciliator is to detect the presence of faults on the existing physical sensors and hide the corrupted measurements in the generation of a virtual output, which one would like to be generated in a reliable way in spite of fault occurrences and hence trustfully usable for control purposes. The sensor faults here considered are limited to variations of both sensor gain and offset values. The proposed approach envisages the use of an unknown input observers coupled with an ‘ad-hoc’ parameters estimator used to estimate online the sensor effectiveness matrix at each time instant. In the paper, two design methodologies are described, based one on the linear parameter varying polytopic formulation and the other on the linear fractional transformation paradigm. All main properties of the considered schemes are investigated and rigorously proved.

ACS Style

Hamid Behzad; Alessandro Casavola; Francesco Tedesco; Mohammad Ali Sadrnia. Fault-tolerant sensor reconciliation schemes based on unknown input observers. International Journal of Control 2018, 93, 669 -679.

AMA Style

Hamid Behzad, Alessandro Casavola, Francesco Tedesco, Mohammad Ali Sadrnia. Fault-tolerant sensor reconciliation schemes based on unknown input observers. International Journal of Control. 2018; 93 (3):669-679.

Chicago/Turabian Style

Hamid Behzad; Alessandro Casavola; Francesco Tedesco; Mohammad Ali Sadrnia. 2018. "Fault-tolerant sensor reconciliation schemes based on unknown input observers." International Journal of Control 93, no. 3: 669-679.

Conference paper
Published: 01 June 2018 in 2018 European Control Conference (ECC)
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ACS Style

Alessandro Casavola; Emanuele Garone; Francesco Tedesco. On the Link Between Multi-Coloring Problems for Graphs and Distributed Supervision of Interconnected Systems. 2018 European Control Conference (ECC) 2018, 1 .

AMA Style

Alessandro Casavola, Emanuele Garone, Francesco Tedesco. On the Link Between Multi-Coloring Problems for Graphs and Distributed Supervision of Interconnected Systems. 2018 European Control Conference (ECC). 2018; ():1.

Chicago/Turabian Style

Alessandro Casavola; Emanuele Garone; Francesco Tedesco. 2018. "On the Link Between Multi-Coloring Problems for Graphs and Distributed Supervision of Interconnected Systems." 2018 European Control Conference (ECC) , no. : 1.

Article
Published: 20 February 2018 in International Journal of Robust and Nonlinear Control
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In this paper, a distributed command governor (CG) strategy is introduced that, by the use of graph colorability theory, improves the scalability property and the performance of recently introduced distributed noncooperative sequential CG strategies. The latter are characterized by the fact that only 1 agent at a decision time is allowed to update its command, whereas all the others keep applying their previously computed commands. The scalability of these early CG distributed schemes and their performance are limited because the structure of the constraints is not taken into account in their implementation. Here, by exploiting the idea that agents that are not directly coupled by the constraints can simultaneously update their control actions, the agents in the network are grouped into particular subsets (turns). At each time instant, on the basis of a round-robin policy, all agents belonging to a turn are allowed to update simultaneously their commands, whereas agents in other turns keep applying their previous commands. Then, a turn-based distributed CG strategy is proposed and its main properties are analyzed. Graph colorability theory is used to determine the minimal number of turns and to distribute each agent in at least a turn. A novel graph colorability problem that allows one to maximize the frequency at which agents can update their commands is proposed and discussed. A final example is presented to illustrate the effectiveness of the proposed strategy.

ACS Style

Alessandro Casavola; Emanuele Garone; Francesco Tedesco. A distributed command governor based on graph colorability theory. International Journal of Robust and Nonlinear Control 2018, 28, 3056 -3072.

AMA Style

Alessandro Casavola, Emanuele Garone, Francesco Tedesco. A distributed command governor based on graph colorability theory. International Journal of Robust and Nonlinear Control. 2018; 28 (8):3056-3072.

Chicago/Turabian Style

Alessandro Casavola; Emanuele Garone; Francesco Tedesco. 2018. "A distributed command governor based on graph colorability theory." International Journal of Robust and Nonlinear Control 28, no. 8: 3056-3072.

Conference paper
Published: 01 January 2018 in Proceedings of the 15th International Conference on Informatics in Control, Automation and Robotics
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ACS Style

Hamid Behzad; Alessandro Casavola; Francesco Tedesco; Mohammad Ali Sadrnia; Gianfranco Gagliardi. A Fault-Tolerant Sensor Reconciliation Scheme based on Self-Tuning LPV Observers. Proceedings of the 15th International Conference on Informatics in Control, Automation and Robotics 2018, 1 .

AMA Style

Hamid Behzad, Alessandro Casavola, Francesco Tedesco, Mohammad Ali Sadrnia, Gianfranco Gagliardi. A Fault-Tolerant Sensor Reconciliation Scheme based on Self-Tuning LPV Observers. Proceedings of the 15th International Conference on Informatics in Control, Automation and Robotics. 2018; ():1.

Chicago/Turabian Style

Hamid Behzad; Alessandro Casavola; Francesco Tedesco; Mohammad Ali Sadrnia; Gianfranco Gagliardi. 2018. "A Fault-Tolerant Sensor Reconciliation Scheme based on Self-Tuning LPV Observers." Proceedings of the 15th International Conference on Informatics in Control, Automation and Robotics , no. : 1.

Conference paper
Published: 01 January 2018 in Proceedings of the 15th International Conference on Informatics in Control, Automation and Robotics
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This paper presents a fault-tolerant sensor reconciliation scheme for systems equipped with a redundant number of possibly faulty ”physical” sensors. The reconciliator is in charge to discover on-line, at each time instant, the faulty physical sensors, if any, and exclude their measures from the generation of the ”virtual” sensors, which, on the contrary, are supposed to be always healthy and suitably usable for control purposes without requiring the reconfiguration of the nominal control law. Amongst many, the solution proposed here is based on the use of a Linear Parameter Varying Luenberger Observers (LPV-LU) able to estimate both state, bias fault and loss of effectiveness fault. Such information is used to self adapting the parameters of the LPV representation. For simplicity, the sensor faults here considered are limited to variation of sensors’ gain and offset values. The scheme is fully described and all of its properties investigated and proved. Finally, a simulation example

ACS Style

Hamid Behzad; Alessandro Casavola; Francesco Tedesco; Mohammad Ali Sadrnia; Gianfranco Gagliardi. A Fault-Tolerant Sensor Reconciliation Scheme based on Self-Tuning LPV Observers. Proceedings of the 15th International Conference on Informatics in Control, Automation and Robotics 2018, 111 -118.

AMA Style

Hamid Behzad, Alessandro Casavola, Francesco Tedesco, Mohammad Ali Sadrnia, Gianfranco Gagliardi. A Fault-Tolerant Sensor Reconciliation Scheme based on Self-Tuning LPV Observers. Proceedings of the 15th International Conference on Informatics in Control, Automation and Robotics. 2018; ():111-118.

Chicago/Turabian Style

Hamid Behzad; Alessandro Casavola; Francesco Tedesco; Mohammad Ali Sadrnia; Gianfranco Gagliardi. 2018. "A Fault-Tolerant Sensor Reconciliation Scheme based on Self-Tuning LPV Observers." Proceedings of the 15th International Conference on Informatics in Control, Automation and Robotics , no. : 111-118.