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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 me...

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.

Over the last decade, the increased use of information and communication technology (ICT) in agriculture applications has led to the definition of the concept of precision farming or equivalently smart agriculture. In this respect, the latest progress in connectivity, automation, images analysis and artificial intelligence allow farmers to monitor all production phases and, due to the help of automatic procedures, determine better treatments for their farms. One of the main objectives of a smart agriculture system is to improve the yield of the field. From this point of view, the Internet of Things (IoT) paradigm plays a key role in precision farming applications due to the fact that the use of IoT sensors provides precise information about the health of the production. In this paper, the results of the recently concluded R&amp, D project ENOTRIA TELLUS are reported. The project aimed at the development of all hardware/software components for implementing a precision farming architecture allowing the farmers to manage and monitor the vineyards’ health status. The smart architecture combines various sub-systems (web application, local controllers, unmanned aerial vehicles, multi-spectral cameras, weather sensors etc.) and electronic devices, each of them in charge of performing specific operations: remote data analysis, video processing for vegetation analysis, wireless data exchanges and weather and monitoring data evaluation. Two pilot sites were built where the smart architecture was tested and validated in real scenarios. Experimental activities show that the designed smart agriculture architecture allowed the farmers to properly schedule the various phases of cultivation and harvesting.

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.

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.

This paper reports the results of a recently concluded R&amp, 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&rsquo, 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.

High penetration of Distributed Generation (DG) plants in Medium Voltage (MV) / Load Voltage (LV) power grids may lead to abrupt voltage raises. Typical critical scenarios are represented by either low demand conditions or high power production from renewable sources. Traditional approaches used to face such a situation involve both the disconnection of the distributed generators and the curtailment of the generated power leading to several disadvantages. However, new technologies allow an active orchestration between some controllable devices of the grid, e.g. distributed generators, MV/HV transformers, storage devices in order to maintain relevant system variables within prescribed operative constraints in response to unexpected adverse conditions. This work addresses the online management of distributed generators and storage devices. The approach is based on Command Governor (CG) ideas and is based on the resolution at each time instant of an optimization problem containing explicit constraints related to voltage bounds and operational limits of adopted devices.

Summary A novel distributed command governor (CG) supervision strategy relying on iterative optimization procedure is presented for multi-agent interconnected linear systems subject to pointwise-in-time set-membership coordination constraints. Unlike non-iterative distributed CG schemes, here all agents undertake several optimization iterations and data exchange before arriving to the optimal solution. As a result, these methods are able to achieve Pareto-optimal solutions not only in steady-state conditions as the ones based on non-iterative optimization procedures but also during transients and are not hampered by the presence of undesirable Nash-equilibria or deadlock situations. The main properties of the method are fully investigated and in particular its optimality, stability, and feasibility properties rigorously proved. A final example is presented where the proposed distributed solution is contrasted with existing centralized and distributed non-iterative CG solutions. Copyright © 2017 John Wiley & Sons, Ltd.

High penetration of distributed generation (DG) in medium voltage (MV) power grids may easily lead to abrupt voltage raises in the presence of either low demand conditions or high power production from renewable sources. In order to cope with the possibly occurring voltage limit violation, the active power injected by the distributed generators is typically curtailed, being, however, such an approach suboptimal from an economical point of view and presenting several other disadvantages. To address this issue, the online management and coordination of the reactive power injected/absorbed by the distributed generators acting on the grid are proposed here. The approach is based on command governor ideas that are used here to optimally solve constrained voltage control problems in both centralized and distributed ways. The approach foresees an active coordination between some controllable devices of the grid, e.g., distributed generators and MV/high voltage transformers, in order to maintain relevant system variables within prescribed operative constraints in response to unexpected adverse conditions. Simulation results show that the proposed approach is more effective than approaches suggested by the current Italian norms on DGs connection.

A significant amount of energy induced by road unevenness and vehicle roll and pitch motions is usually dissipated by conventional shock-absorbers. In this paper, a novel active multiobjective H∞ c...

This paper focuses on the design and implementation on low-cost embedding systems of the overall signal processing chain required for the estimation of the turbocharger rotating speed from the overall sound emissions acquired via a microphone placed in the vehicle hood. Because the useful information about the turbo speed is disturbed by all other noisy subsystems of the engine and powertrain, 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 signal. Fixed-point vs floating-point implementations have been compared in several tests. Experimental outcomes demonstrate that the approach is ready to be introduced in the Engine Control Unit (ECU) in order to achieve new strategies for the turbocharger control.

In underwater localization several sources of error may impact in different ways the final estimation of the position. This applies to the Long Baseline (LBL), the Short Baseline (SBL) and the Ultra-Short Baseline (USBL) localization systems. Through simulations and statistical analysis, it is possible to identify and experimentally characterize such sources of error. It could be also investigated how much these sources of error influence the estimation results of an Extended Kalman Filter (EKF). This paper presents the results of experiments designed in a virtual environment, useful to represent real localization systems. Specifically, the system used for the simulation is constituted by a surface platform equipped with four acoustic transducers used for the localization of an underwater target.

High penetration of Distributed Generation (DG) in Medium Voltage (MV) power grids is usually a reason of abrupt voltage raises. In this respect critical scenarios are represented by both low demand conditions and high power production from renewable sources. In order to cope with the possibly resulting voltage limits violation, a typical adopted approach is the disconnection of the distributed generators or the curtailment of the generated power leading to several disadvantages. To address this issue an online management of the reactive power of distributed generators is presented. The approach is based on Command Governor (CG) ideas and is aimed at solving a constrained voltage regulation problem in both centralized and distributed ways. The approach foresees an active coordination between some controllable devices of the grid, e.g. distributed generators, MV/HV transformers, in order to maintain relevant system variables within prescribed operative constraints in response to unexpected adverse conditions. Simulation results show that the proposed approach is more effective than approaches suggested by the current Italian norms on reactive power compensation.

© 2016 Published by Elsevier Ltd on behalf of International Federation of Automatic Control.Economic Model Predictive Control is a technique for optimization of economic revenues arising from controlled dynamical processes that has established itself as a variant of standard Tracking Model Predictive Control. It departs from the latter in that arbitrary cost functions are allowed in the formulation of the stage cost. This paper takes a further step in expanding the applicability of Economic Model Predictive Control by illustrating how the paradigm can be adapted in order to accommodate time-varying or parameter-varying costs.

This paper presents the initial stage of the development of an underwater localization system suitable for a flexible number of users. Multiple Autonomous Underwater Vehicles (AUVs) can work as a team and cooperate with other teams of AUVs without costly and acoustically active components, which saves energy and allows AUVs to remain silent. The main building blocks for such a system are: spiral wavefront beacon in conjunction with a standard (circular) acoustic modem, Chip Scale Atomic Clocks (CSAC), acoustic modems, state-of-the-art adaptive underwater networking and Cooperative Localization (CL) algorithms. Using the difference in time of arrival between the spiral wavefront and the modem circular wavefront, receivers will be able to determine the bearing to the source using only one hydrophone. Synchronizing vehicles Chip Scale Atomic Clocks (CSAC) with the beacon at the beginning of the mission and during the longer missions will ensure the vehicles ability to also calculate their distance from the beacon upon every message reception.

Community-based microgrid (C- $\mu $ Grid) systems are gaining increasing importance nowadays because of the lack of $\mu $ Grid public investment and management policies. Technoeconomic analysis shows that C- $\mu $ Grid based on a cluster of microgenerators could be an effective solution when individual systems are not feasible. In this paper, the controlling capability of the central controller of the C- $\mu $ Grid is improved through an economic model predictive control (EMPC) approach operating at the pricing level that can fulfill the goal of the operational control of the cluster. With a central controller, it is capable of satisfying the demand at prosumer (active energy producer and simultaneous consumer) sides and, at the same time, optimizing the various $\mu $ Grid contrasting constraints. Emphasis here has been given to the operational constraints related to the battery lifetime, so that the maintenance and replacement costs would be reduced. A comparative analysis has been carried out between the performance of two systems, one based on an IF-THEN-ELSE heuristic supervision logic (S-LOGIC) and the other based on the proposed EMPC strategy. The analysis has been undertaken in a location in Dublin, Ireland, on the basis of available measured data. Simulation shows the effectiveness of implementing the EMPC approach to optimally manage the system.

Regulation problems for networked constrained polytopic Linear Parameter Varying (LPV) systems are considered. It is assumed that the communication network is subject to latency effects which result in induced time-varying time-delays on both the control and measurement channels. A novel LPV customization of a recent Receding-Horizon control (RHC) scheme developed for polytopic uncertain linear systems is here proposed. It exploits the LPV scheduling parameter availability for pre-computing nested families of one-step ahead controllable ellipsoidal sets, which are significantly less conservative than their robust counterparts. Finally, simulation results concerning the constrained regulation of a unicycle-type mobile robot are reported to show the effectiveness and the benefits of the proposed control scheme.

Distributed Generation (DG) has gained relevance In Medium Voltage (MV) / Low Voltage (LV) power grids worldwide. One of the main drawbacks related to high penetration of DG plants is represented by abrupt voltage raises. Such an issue typically occurs in the presence of either low demand conditions or high power production from renewable sources. This work is focused on the online management of distributed generators and storage devices and exploits ideas of the Distributed Command Governor (DCG) approach, which is mainly based on the resolution at each time instant of an optimization problem minimizing management costs and containing explicit constraints on voltage bounds and operational ranges of relevant grid devices.

This paper concerns the implementation of an efficient underwater acoustic network suitable for long lasting environmental monitoring in fish farming. Several hardware and software solutions have been designed and implemented to extend the network lifetime and to make the system autonomous and suitable for such an application scenario. The proposed system is composed of different components. The SUNSET Software Defined Communication Stack (SDCS) is used to provide networking capabilities to underwater nodes communicating acoustically through AppliCon SeaModem modems. The Hydrolab Series 5 probes are used to monitor the water quality. Lifetime of underwater nodes is extended through the use of a novel device that allows to harvest energy from underwater water currents via suitable propellers. In addition, novel sleep and wake up mechanisms have been designed and implemented into the underwater nodes to minimize the energy consumption of the system during the idle periods. The performance of the proposed system has been extensively evaluated in field by monitoring the water quality in three fish farming cages located in the Mediterranean Sea, Italy. The system has been connected to the Internet infrastructure allowing the users to easy interact with the underwater system in real-time. Our results confirm that the proposed system is suitable for long term monitoring providing a reliable and robust data collection scheme with an extended network life time.

The chapter concerns the solutions of lane detection (LD) and lane tracking (LT) problems that are relevant in the implementation of lane departure warning systems (LDWSs), a kind of advanced driver assistance systems (ADASs) finalized to warn the driver that an imminent and possibly unintentional lane departure is taking place. The proposed solutions are based on simple image processing algorithms that work on the frames of a video stream of the oncoming road sections taken by a camera mounted on the front windshield of the vehicle. LD algorithms are finalized to identify the stripes demarcating the lane within a single frame, whereas LT algorithms try to track the demarcating stripes in subsequent frames of the stream. Final simulations on the software simulator CarSim 8 are also provided at the end of the chapter under realistic driving scenarios.

A novel distributed coordination strategy is presented for networked, locally regulated and possibly dynamically coupled, interconnected systems. Such systems are assumed to be connected via data links and subject to pointwise-in-time global constraints on some relevant variables of them, to be enforced as a coordination goal along the overall system evolutions. Such a coordination-by-constraint paradigm is accomplished by resorting to a novel distributed multi-agent Command Governor (CG) approach where each agent is in charge to locally modify, whenever necessary and on the basis of a reduced amount of data exchanged with the other agents, the prescribed set-points to the regulated subsystems so that the coordination constraints are always satisfied. The strategy is described and its main properties analyzed, especially for what it concerns the stability, feasibility and Pareto optimality of the solution. A liveness analysis concerning the possible presence of undesirable Nash equilibria and/or deadlock situations is presented and a discussion on the scalability of the solution with the problem dimension is reported as well. The constrained coordination of a network of interconnected water tanks is presented as a final example in order to show the effectiveness of the proposed strategy. © 1963-2012 IEEE.

Summary An application of a recently proposed fault detection and isolation (FDI) design methodology for linear parameter varying (LPV) systems is presented which concerns the robust detection of stator windings faults of an electrical induction motor regulated by a speed controller. On the basis of a detailed nonlinear mathematical model of the motor, it is shown how, based on a judicious convex interpolation of a family of linearized models, a quasi-linear parameter varying (quasi-LPV) approximation capable to catch most of the nonlinearities of the model can be achieved and can directly be used for synthesizing LPV-FDI observers. The design methodology consists in solving a multi-objective convex linear matrix inequalities optimization problem where disturbance rejection and fault sensitivity are traded-off in suitable frequency regions. The resulting diagnostic observer is gain-scheduled and uses a set of motor variables, assumed measurable online, as a scheduling vector. The effectiveness of the LPV-FDI framework is illustrated in a final numerical example. Copyright © 2014 John Wiley & Sons, Ltd.

SUMMARY A distributed supervisory strategy for addressing load/frequency set-point reconfiguration problems in networked multi-area microgrid is presented. The aim is at finding a distributed coordination strategy able to reconfigure, whenever necessary in response to unexpected load changes and/or faults, the nominal set-point on frequency and generated power to the generators of each area so that viable evolutions arise for the overall power system during transients and a new post-fault sustainable equilibrium is reached. In order to demonstrate the effectiveness of the strategy, an example on a four-area power system is presented. Copyright © 2014 John Wiley & Sons, Ltd.

This technical note presents an improved version of the Feed-Forward Command Governor (FF-CG) strategy recently proposed in for the supervision of input/state constrained discrete-time linear systems subject to bounded disturbances, whose main feature is not to require any explicit on-line measure (or estimation) of the state for its implementation. Although effective also in the case of bounded disturbances, the performance of earlier FF-CG schemes was mainly limited by the fact that such strategies were required to maintain constant their actions for a prescribed number of sampling steps. Here such a restriction is removed and the proposed FF-CG solution is allowed to update its action at each sampling step. Numerical simulations on a physical plant have been undertaken and comparisons with other strategies have been reported in order to show the effectiveness of the proposed approach.

SUMMARY In this paper, we propose a fault detection and isolation filter design method for internal combustion spark ignition engines. Starting from a detailed nonlinear mean-value mathematical description of the engine, a novel linear parameter varying (LPV) model approximation is derived on the basis of a judicious convex interpolation of a family of linearized models. A filter structure consisting of a bank of LPV observers is considered, each of them in charge of detecting a particular class of faults and exhibiting low sensitivity to all other faults and exogenous inputs. The resulting diagnostic filter is parameter-dependent in that a set of measurable engine variables is used online to suitably modify the filter gain so as to better take care of system nonlinearities. The quality of the LPV model approximation of the engine and the diagnostic capabilities of the fault detection and isolation architecture are demonstrated by a series of extensive numerical simulations. Copyright © 2013 John Wiley & Sons, Ltd.

In this paper, we present a novel control architecture capable to deal with the constrained Load Frequency Control (LFC) problem in a distributed way and to jointly manage time-delay attacks on the communication links existing amongst power areas and a set of high level controllers located at remote sides. The starting idea consists in abstractly modeling the power grid as a leader-follower configuration so that a first input -first output protocol can be adopted to compute adequate control actions. The latter is achieved by resorting to an overlapping system description which prescribes that several areas of the power grid concur to obtain a single element of the leader-follower structure. The approach is based on to the reachability analysis developed in [3] where sequences of one-step ahead controllable sets have been formally derived by taking into account existing state/input constraints, distributed structure of the problem and data loss occurrences due to possible cyber attacks. Simulations put in light the reconfiguration capabilities of the proposed framework that allow one to “isolate” the attacked power units which in principle could compromise the overall operation mode of the power grid.

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 possibly faulty physical sensors 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 Unknown Input Observers (LPV-UIO) coupled with an “ad-hoc” parameter estimator used to identify on-line the current sensor reconciliation matrix. The latter is therefore used to hide the faulty measures from the pool of physical outputs in the generation of the virtual outputs. 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 is reported in details to show the effectiveness of the scheme.

This paper presents the initial implementation of an acoustic synchronization and ranging system to enable the control and cooperation of multiple Unmanned Underwater Vehicles (UUVs). Our solution is based on acoustic clock synchronization and one-way ranging. It requires minimum overhead while providing accurate and quick estimation of the relative distances among underwater nodes. The use of one-way ranging allows to scale up to large teams of UUVs and reduces the energy consumption of localization techniques. Our solution has been implemented in SUNSET, leveraging on the accurate timing information and scheduled transmissions provided by SeaModem acoustic modems. Chip Scale Atomic Clocks have been integrated in the SeaModem to overcome the typical drift of real-time clocks thus enabling accurate one-way ranging estimation during long term missions. The performance of the proposed system have been extensively evaluated in two at-sea campaigns considering different testing scenarios. We have shown that our scheme is able to maintain high ranging accuracy over time without requiring the high overhead and energy consumption of two way ranging techniques. We have also shown that the proposed scheme for acoustic synchronization is very effective in synchronizing real-time and atomic clocks of underwater nodes, whenever needed. Our results confirm that the proposed solution for synchronization and one-way ranging allows to enable the control of multiple UUVs keeping at the bay the overhead in the network and the time needed to estimate relative distances.

A novel multiobjective ℋ ∞ state-feedback control design methodology is proposed which includes, besides the usual control objectives on ride comfort, road handling and suspension stroke, the amount of energy to be harvested as a further conflicting objective and allows the designer to directly trade-off among them depending on the application. An electromechanical regenerative vehicle suspension system is considered where the viscous damper is replaced by a linear electrical motor which is actively governed. It is shown that the proposed control law is able to achieve remarkably improvements on the amount of harvested energy with respect to passive or semi-passive control strategies while maintaining the other objectives at acceptable levels. It is also shown how the state-feedback design can be converted into a 2DOF dynamic output feedback control strategy by using a suitable state observer. Simulative studies undertaken via Simulink are finally reported that confirm the potentiality and flexibility of the proposed control design strategy.

In this paper we present an application to an electrical induction motor of a recently proposed gain-scheduling Fault Detection and Isolation (FDI) filter design method for LPV systems. Starting from a detailed nonlinear mathematical representation of the motor it is shown how, based on a judicious convex interpolation of a family of linearized models, a quasi-LPV approximation can be achieved and used for synthesizing the LPV-FDI filter. The latter is then synthesized by ensuring guaranteed levels of disturbance rejection and fault detection and isolation sensitivity. The resulting diagnostic filter is gain-scheduled and uses a set of motor variables, assumed measurable on-line, as a scheduling vector. The effectiveness of the LPV-FDI framework is illustrated by a numerical example.

This paper proposes a novel class of Command Governor (CG) strategies for input and state-related constrained discrete-time LTI systems subject to bounded disturbances in the absence of explicit state or output measurements. While in traditional CG schemes the set-point manipulation is undertaken on the basis of either the actual measure of the state or its suitable estimation, it is shown here that the CG design problem can be solved, with limited performance degradation and with similar properties, also in the case that such an explicit measure is not available. This approach, which will be referred to as the Feed-Forward CG (FF-CG) approach, may be a convenient alternative CG solution in all situations whereby the cost of measuring the state may be a severe limitation, e.g. in distributed or decentralized applications. In order to evaluate the method proposed here, numerical simulations on a physical example have been undertaken and comparisons with the standard state-based CG solution reported.

SUMMARY A fault detection and isolation (FDI) filter design method is proposed for linear parameter-varying (LPV) systems, which are subject to abrupt changes in their structure. Such a phenomenon is modeled by a finite state Markov chain whose outcome is supposed to be directly available along with its rates transition matrix. The FDI filter is designed as a bank of ℋ−/ℋ∞ Luenberger observers, derived by optimizing frequency conditions that ensure guaranteed levels of disturbance rejection, fault sensitivity and are capable to discriminate anomalous events belonging to different fault classes. It is proved that, by resorting to stochastic stability concepts, the design method can be recast as a linear matrix inequality programming program in the observer bank gains. The resulting residual generator is a jump parameter-dependent observer jointly exploiting the available measures on the deterministic plant parameter and on the instantaneous Markov chain realization. An FDI threshold logic is also proposed in order to reduce the generation of false alarms. The effectiveness of the design technique is illustrated via a numerical example. Copyright © 2011 John Wiley & Sons, Ltd.

A distributed constrained supervisory strategy for large-scale spatially distributed systems is presented and applied to a networked water distribution system. The aim is at reconfiguring, whenever necessary in response to different supply downstream demands, the nominal set-points to the tank water levels so that all prescribed coordination and operational constraints are enforced during the system evolutions and sustainable equilibria are reached. The presented supervision strategy follows a coordination-by-constraint approach and is based on Feed-Forward Command Governor (FF-CG) ideas. The effectiveness of the strategy is shown in the final example where the supervision of an eight-tank interconnected system is considered.

In this paper we present a novel distributed supervision strategy for multi-agent linear systems connected via data networks and subject to coordination constraints. Such a coordination-by-constraint paradigm is based on an on-line active set-point management and is characterized by a set of spatially distributed dynamic systems, connected via communication channels, with possibly dynamical coupling amongst them which need to be supervised and coordinated in order to accomplish their overall objective. Two distributed strategies will be fully described and analyzed. First, we will propose a “sequential” distributed strategy in which only one agent at the time is allowed to manipulate its own reference signal. Such a strategy will be instrumental to introduce a more effective “parallel” distributed strategy, in which all agents are allowed, under certain conditions, to modify their own reference signals simultaneously. To show the effectiveness of the proposed methods, the distributed coordination of dynamically coupled autonomous vehicles under input-saturation and formation accuracy constraints is presented.

This paper proposes a novel class of Command Governor (CG) strategies for input/state constrained linear systems subject to bounded disturbances in the absence of explicit state measurement or its estimation. While in traditional CG schemes, the setpoint manipulation is undertaken on the basis of either the actual measure of the state or of its suitable estimation, it is shown here that the CG design problem can be solved with limited performance degradation and with similar properties also in the case that such an explicit measure is not available, by forcing the state evolutions to stay “not too far” from the manifold of feasible steady-states. This approach, which will be referred to as Feed Forward CG (FF-CG), may be a convenient alternative CG solution in all situations whereby the cost of measuring the state may be a severe limitation, e.g. in distributed or decentralized applications. In order to evaluate the method here proposed, numerical simulations on a physical plant have been performed and comparisons with the standard state-feedback CG solution reported.

This paper presents a fault-tolerant adaptive control allocation scheme for overactuated systems subject to loss of effectiveness actuator faults. The main idea is to use an ‘ad hoc’ online parameters estimator, coupled with a control allocation algorithm, in order to perform online control reconfiguration whenever necessary. Time-windowed and recursive versions of the algorithm are proposed for nonlinear discrete-time systems and their properties analyzed. Two final examples have been considered to show the effectiveness of the proposed scheme. The first considers a simple linear system with redundant actuators and it is mainly used to exemplify the main properties and potentialities of the scheme. In the second, a realistic marine vessel scenario under propeller and thruster faults is treated in full details. Copyright © 2010 John Wiley & Sons, Ltd.

This paper deals with a distributed coordination problem including collision avoidance. The problem is solved by using a Command Governor strategy based on mixed integer optimization. First, we present an algorithm to find an appropriate command in the centralized case, then a distributed sequential procedure is described. Simulations are reported for comparisons.

In this paper we present preliminary ideas on how to develop distributed supervision strategies for networked control systems subject to coordination constraints to be enforced on-line. Such a coordination paradigm, hereafter referred to as coordination-by-constraint , is characterized by a set of spatially distributed dynamic systems, connected via communication channels, with possibly dynamical coupling amongst them which need to be supervised and coordinated in order to accomplish their overall objective. In order to evaluate the distributed method here proposed, the distributed coordination of coupled autonomous vehicles under input-saturation and formation accuracy constraints is presented as an example.

In this paper we present a supervisory strategy for load/frequency control problems in networked multi-area electrical power systems. The proposed strategy exploits a recently developed constrained control methodology named Parameter Governor, which is based on predictive control ideas and combines in a unique framework the actions of Reference and Offset Governors. The supervisor reconfigures the nominal frequency set-points and adds offsets to the input terminals of the generation units of each area in order to avoid operative constraint violations when unexpected load changes and/or failures occur. Such a reconfiguration capability is achieved by exploiting the inherent physical redundancy of the power grid and allows, if effective, the enhancement of the overall fault tolerance. 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. Copyright © 2008 John Wiley & Sons, Ltd.

A novel fault detection and isolation (FDI) filter design method is proposed for linear parameter varying (LPV) systems. The LPV system description can be used to approximate the behavior of nonlinear systems and leads to simple nonlinear FDI designs. The main goal here is to obtain residual generator (RG) filters with enhanced fault transmission dc-gains and large ℋ∞ nuisance attenuation. This is achieved using bilinear matrix inequality techniques by exploiting the relevant geometrical properties of the affine LPV description. Finally, it is shown by a nonlinear example that the RG filters designed by the proposed method compare well with alternative approaches including direct nonlinear design methods. Copyright © 2008 John Wiley & Sons, Ltd.

This paper deals with the design of a residual generator (RG) for linear time-invariant systems subject to simultaneous different faults, disturbances and measurement noises. The objective is to design an RG filter that maximizes the transmission from a potential fault to a related residual, while minimizing the ones from nuisances (disturbances, measurement noises and other faults). The isolation of each fault is carried out by designing a bank of RG filters, each one insensitive, as much as possible, to nuisances and capable of detecting the occurrence of its related fault. The design is carried out through ℋ∞ filtering techniques under an eigenstructure assignment constraint. Under mild assumptions, the RG filter can be obtained by solving a λ-parameterized linear matrix inequality optimization problem. A comparison with existing fault detection and isolation (FDI) methods is considered in order to exhibit the relative merits of the proposed method. Copyright © 2008 John Wiley & Sons, Ltd.

In this paper we present a supervisory strategy for voltage regulation control problems in electrical power grids based on the Command Governor (CG) approach. The scheme consists of reconfiguring the nominal voltage set-point of the network in the presence of Distributed Generation (DG) units to avoid operative constraint violations in response to unexpected load changes and/or failures. Such a reconfiguration capability allows one to enhance the fault tolerability and to prevent undesirable phenomena from occurring in the electrical power grid. We focus on an electrical Medium Voltage (MV) distribution network subject to coordination constraints on maximum load voltages deviations and possible failures on the on-load tap changers (OLTC). Simulation results show that the CG unit ensures feasible evolutions of the overall network by reconfiguring the nominal voltage set-point, whenever critical events occur.

This paper presents a preliminary adaptive control allocation scheme for overactuated autonomous vehicles that is fault-tolerant with respect to actuator faults or loss of effectiveness. The main idea here is to use an ad-hoc online parameter estimator coupled with an allocation algorithm to perform on-line control reconfiguration. A simple algorithm is proposed for nonlinear discrete-time systems and its main properties are summarized for the disturbance-free case. Its effectiveness is also investigated by means of numerical simulations on an underwater vehicle.

In this paper a constrained control strategy based on predictive control ideas is used to regulate the voltage in electrical Medium Voltage (MV) power networks. The aim is to regulate the voltage at certain nodes of the network in the presence of Distributed Generation (DG) units and despite of various changing loads acting as exogenous disturbances. The voltage regulation problem is rephrased as a constrained tracking control problem by imposing that the voltages at certain loads have minimum deviation from their nominal values. Simulations studies show the effectiveness of the proposed approach.

This paper provides a tutorial overview of a number of aspects and approaches to Control over the Network for Network Control Systems (NCS) that are likely to lead to good fault-tolerant control properties, subject to network faults. In order to analyze and derive the best strategies for fault tolerant NCS, it is initially assumed that the network communication bandwidth is infinite. This gives a simpler way to map the NCS structure in terms of computing nodes and control subsystems/components. Two Fault-tolerant NCS architectures have been described, analyzed and compared with view to demonstrating that the classical concepts of Fault-tolerant Control (FTC), namely of active and passive FTC can be related to equivalent (although more complex) concepts in NCS. The study confirms that the de-centralized approach to faulttolerant control of NCS suffers from a difficult challenge as to how to compensate for fault effects occurring throughout the NCS. On the other hand, the distributed hierarchical structure, requires a coordination function which is able to manage (a) the local control task, (b) the compensation of faults, and (c) the network reconfiguration, if required, subject to significant network subsystem faults.

In this paper we present the initial implementation of an advanced communication and networking solution that can enable the coordination and cooperation of autonomous mobile marine robots. To enable such a heterogeneous network three main research areas have been blended: 1) communications, 2) networking, and 3) decentralized cooperative localization and control. This paper focuses on the first two components and addresses the integration of the third one. Due to the challenges of the underwater environment, novel communication software and hardware have to be investigated to provide the level of flexibility and features that are required for efficient networking and robots cooperation. Robust and reliable distributed networking protocols have to be developed and implemented to enable an efficient sharing of data and control messages among heterogeneous surface and underwater platforms. Moreover, the combination of communications, networking and cooperative navigation has to be addressed in order to develop more capable, distributed and efficient underwater systems.

SeaModem is a low-cost underwater acoustic modem developed by AppliCon, a spin-off of the University of Calabria, for shallow water communications. In its default configuration, it operates in the 25–35 KHz frequency range and offers a wide range of selectable features including selectable 2-4-8 FSK modulation tones, error detection and correction algorithms via CRC and Viterbi, selectable power transmission up to 40 W, one-way and two-way range calculation capabilities, network capabilities allowing communications among a maximum of 15 modems in the same area and a host interface via a configurable UART. The paper contains a detailed description of the system and the results of several tests are also provided.

In this paper, we present a predictive strategy for teleoperating through communication channels with unknown and possibly unbounded time delay, a remotely located precompensated plant subject to input and state-related pointwise-in-time constraints. The significance of the method is that it is capable of generating command signals such that, once received and applied to the remote plant, stability is preserved and no constraints violation occurs regardless of any possible time delay. The method can be further specialized to deal either with bounded time delay, as typically encountered in space and underwater applications, or with random and possibly unbounded roundtrip time delay, as in the Internet case. In order to demonstrate its effectiveness, a master/slave teleoperation problem over the Internet is considered. It consists of stabilizing via teleoperation a cart/rod inverted pendulum under cart motor voltage and rod angle constraints, through a communication link affected by time delay.

In this paper, we present a discrete-time predictive control strategy for the supervision of networked dynamic systems subject to coordination constraints. Such a network paradigm is characterized by a set of spatially distributed systems, possibly dynamically coupled and connected via communication links, which need to be controlled and coordinated in order to accomplish their overall objective. The network latency is modeled abstractly as a time-varying time-delay, which is allowed to become unbounded for taking into account data-loss. The method can be specialized to deal more efficiently either with random, possibly unbounded, time-delays, such as the case over the Internet, or constant/bounded time-delays, typically encountered in space and underwater applications. An example of coordination of two autonomous vehicles under input-saturation and formation accuracy constraints is presented.