Integrated fault estimation and accommodation design for discrete-time Takagi-Sugeno fuzzy systems with actuator faults

This paper addresses the problem of integrated robust fault estimation (FE) and accommodation for discrete-time Takagi–Sugeno (T–S) fuzzy systems. First, a multiconstrained reduced-order FE observer (RFEO) is proposed to achieve FE for discrete-time T–S fuzzy models with actuator faults. Based on the RFEO, a new fault estimator is constructed. Then, using the information of online FE, a new approach for fault accommodation based on fuzzy-dynamic output feedback is designed to compensate for the effect of faults by stabilizing the closed-loop systems. Moreover, the RFEO and the dynamic output feedback fault-tolerant controller are designed separately, such that their design parameters can be calculated readily. Simulation results are presented to illustrate our contributions

Fault Tolerant Control Schemes for Wireless Networked Control Systems with an Integrated Scheduler

In recent years, the wireless networked control systems (W-NCSs) has gained increasing popularity in industrial processes. To guarantee the system control performance, fault tolerant control (FTC) strategies have been proposed especially to deal with the malfunction in sensors, actuators or other system components. For the real-time requirement in industrial systems, the FTC performances of W-NCSs not only depend on the developed control algorithms but also on the network protocols at the medium access control (MAC) layer. These protocols, in form of schedulers, determine the transmission orders of messages and play significant roles in the control performances of W-NCSs. Under these circumstances, it is challenging but promising to investigate FTC schemes for W-NCSs with an integrated scheduler. This thesis is devoted to the development of FTC strategies for W-NCSs with an integrated scheduler. In the first part of this thesis, the procedures of integrating a scheduler into W-NCSs are introduced. Due to the requirement for deterministic transmission behaviors via the wireless network, the time division multiple access (TDMA) mechanism is adopted in W-NCSs. The TDMA-based scheduler is taken as a dynamic system and formulated into a periodic system. After that, with the integration of the scheduler, the W-NCSs are modeled as discrete linear time periodic (LTP) systems. The second part of this thesis focuses on the developments of FTC schemes for the integrated LTP systems. Two types of faults, i.e., additive faults (AFs) and multiplicative faults (MFs), are considered in our work. Specifically, a group of fault tolerant controllers are constructed for the AFs case, and seek to ensure that the outputs of LTP systems satisfy a set of H_infty performance indices. On the other hand, a lifting technology and an adaptive observer are applied to handle the situation of MFs. Due to the distribution of W-NCSs and the limitation of communication bandwidth, theorems are presented to solve the structure-restriction problem in the gains of observers and controllers. Finally, the derived FTC approaches are verified on an advanced experimental WiNC (wireless networked control) platform. Following the structure-restricted gains, the FTC strategies are realized with shared and unshared information (i.e., residual signals and state estimates), respectively. The results indicate that the system with shared information has achieved better FTC performances. In den letzten Jahren, haben die drahtlos vernetzten Steuerungssystemen (W-NCSs) sich zunehmender Beliebtheit in industriellen Prozessen gewonnen. Um die Systemsteuerleistung zu gewährleisten, sind die fehlertoleranten Regelung (FTC) Strategien vorgeschlagen worden, um vor allem mit der Fehlfunktion in Sensoren, Aktoren oder andere Systemkomponenten umzugehen. Für die Echtzeitanforderung in industriellen Systemen, hängen die FTC-Leistungen der W-NCSs nicht nur von den entwickelten Regleralgorithmen sondern auch von den Netzwerkprotokollen auf dem Medium Access Control (MAC)-Layer ab. Diese Protokolle, in Form von Schedulers, bestimmen die Reihenfolge der Übertragung der Nachrichten und spielen eine bedeutende Rolle in den Steuerleistungen von W-NCSs. Unter diesen Umständen ist es herausfordernd aber vielversprechend um FTC Regelungen für W-NCSs mit einem integrierten Scheduler zu untersuchen. Diese Arbeit widmet sich auf die Entwicklung von FTC Strategien für W-NCSs mit einem integrierten Scheduler. Im ersten Teil der Arbeit werden die Verfahren der Integration einen Scheduler in W-NCSs eingeführt. Aufgrund der Anforderung deterministisches Übertragungsverhalten über das drahtlose Netzwerk zu gewährleisten, wird der Time-Division-Multiple-Access (TDMA) Mechanismus gewählt. Der TDMA-basierte Scheduler ist als ein dynamisches System betrachtet und als ein Periodisches system formuliert. Danach, mit der Integration des Schedulers, werden die W-NCSs als diskrete Linear Time Periodic (LTP)-Systeme modelliert. Der zweite Teil der Arbeit konzentriert sich auf die Entwicklung der FTC Regelungen für die integrierten LTP-Systeme. Zwei Arten von Fehlern, d.h., additive Fehlern (AFs) und multiplikativen Fehlern (MFs), sind in unserer Arbeit berücksichtigt. Für LTP-Systeme mit AFs wird ein Satz von fehlertoleranten Reglern entworfen, dass die Ausganggröße eine Reihe von H_infty-Leistungsindizes erfüllen werden. Auf der anderen Seite, werden ein Hebetechnik und eine adaptive Beobachter angewendet, um den Fall von MFs zu behandeln. Aufgrund der Verbreitung der W-NCSs und gleichzeitiger Begrenzung der Kommunikationsbandbreite werden Theoreme vorgestellt, um das Problem der Strukturbeschränkung in den Beobachter- bzw. Reglermatrizen zu lösen. Abschließend werden die hergeleiteten FTC-Ansätze auf einem fortgeschrittenen WiNC (drahtlos vernetzten Regelung) Plattform überprüft. Nach den Beobachter- bzw. Reglermatrizen sind die FTC-strategien mit vollständig geteilter oder nicht geteilter Informationen (d.h., Residuum Signale und Schätzungen der Zustandsgrößen) realisiert worden. Die Ergebnisse zeigen, dass das System mit vollständig geteilten Informationen bessere FTC-Leistungen erzielt hat

Distributed fault detection and isolation of large-scale nonlinear systems: an adaptive approximation approach

2007/2008The present thesis work introduces some recent and novel results about the problem of fault diagnosis for distributed nonlinear and large scale systems. The problem of automated fault diagnosis and accommodation is motivated by the need to develop more autonomous and intelligent systems that operate reliably in the presence of system faults. In dynamical systems, faults are characterized by critical and unpredictable changes in the system dynamics, thus requiring the design of suitable fault diagnosis schemes. A fault diagnosis scheme that drew considerable attention and provided remarkable results is the so called model based scheme, which is based upon a mathematical model of the healthy behavior of the system that is being monitored. At each time instant, the model is used to compute an estimate of what should be the current behavior of the system, assuming it is not affected by a fault. If the behavior of the system is characterized by the time evolution of its state vector x(t), and the inputs to the system are denoted as u(t), then the most general nonlinear and uncertain discrete time model can be represented by x(t + 1) = f (x(t), u(t)) + η(t) , where the nonlinear function f represents the nominal model of the healthy system, and η(t) is an uncertainty term. A proven way to compute an estimate of the state x(t) is by using a diagnostic observer, so that in healthy conditions the residual between the true and the estimated value is, in practice, close to zero. Should the residual cross at a certain point a suitable threshold ̄ǫ(t), the observed difference between the model estimate and the actual measurements will be explained by the presence of a fault. The model-based scheme outlined so far has showed many interesting properties and advantages over signal-based ones, but anyway poses practical implementation problems when one tries to apply it to actual distributed, large-scale systems. In fact an implicit assumption about the model-based scheme is that the task of measuring all the state and input vectors components, and the task of computing the estimate of x(t) can be done in real-time by some single and powerful computer. But for large enough systems, this assumptions cannot be fulfilled by available measurement, communication and computation hardware. This problem constitutes the motivation of the present work. It will be solved by developing decomposition strategies in order to break down the original centralized diagnosis problem into many distributed diagnosis subproblems, that are tackled by agents called Local Fault Diagnosers that have a limited view about the system, but that are allowed to communicate between neighboring agents. In order to take advantage of the distributed nature of the proposed schemes, the agents are allowed to cooperate on the diagnosis of parts of the system shared by more than one diagnoser, by using consensus techniques. Chapter 2 introduces the problem of model-based fault diagnosis by presenting recent results about the centralized diagnosis of uncertain nonlinear discrete time systems. The development of a distributed fault diagnosis architecture is covered in the key Chapter 3, while Chapters 4 and 5 show how this distributed architecture is implemented for discrete and continuous time nonlinear and uncertain large–scale systems. In every chapter an illustrative example is provided, as well as analytical results that characterize the performances attainable by the proposed architecture. ---------------------------------------------------Questo lavoro di tesi presenta alcuni risultati recenti ed innovativi sulla diagnostica di guasto per sistemi nonlineari distribuiti e su larga scala. Il problema della diagnostica automatica di guasto è motivata dal bisogno di sviluppare sistemi maggiormenti autonomi e robusti, che possano operare in modo affidabile anche in presenza di guasti. Nei sistemi dinamici, i guasti sono caratterizati da variazioni critiche ed imprevedibili della dinamica, e richiedono perciò la progettazione di schemi di diagnostica adeguati. Uno schema che ha riscosso notevole successo è il cosidetto schema basato su modello, che si fonda su un modello matematico del comportamento sano del sistema sotto osservazione. Ad ogni istante, il modello è usato per calcolare una stima di quello che dovrebbe essere il comportamento attuale, supponendo l’assenza di guasti. Se il comportamento del sistema è caratterizzato attraverso l’evoluzione temporale del vettore di stato x(t), ed il vettore degli ingressi è indicato con u(t), allora il modello più generale per un sistema non lineare ed incerto a tempo discreto è x(t + 1) = f (x(t), u(t)) + η(t) , dove la funzione nonlineare f rappresenta la dinamica del sistema sano, mentre η(t) è l’incertezza di modello. Un modo comprovato per calcolare una stima dello stato x(t) fa uso di un osservatore diagnostico, cosicché in condizioni normali il residuo tra il valore vero e quello stimato è, in pratica, quasi nullo. Se dovesse ad un certo punto superare un’opportuna soglia, la differenza osservata tra la stima del modello ed il valore vero misurato sarebbe spiegabile con la presenza di un guasto. Lo schema basato su modello riassunto finora ha mostrato molte proprietà interessanti e vantaggi rispetto quelli basati su segnali, ma pone in ogni caso problemi di tipo pratico quando lo si voglia applicare a sistemi reali distribuiti e su larga scala. Infatti un’ipotesi sottointesa dello schema basato su modello è che il compito di misurare tutte le componenti di x(t) e di u(t), e quello di calcolare la stima di x(t) possa essere portato a termine in tempo reale da un singolo nodo di calcolo. Nel caso di sistemi sufficientemente vasti, però, questa ipotesi non può essere rispettata da alcuna delle risorse di calcolo disponibili in pratica. Questo problema è alla base del presente lavoro di tesi. Verrà risolto sviluppando delle strategie di decomposizione in modo da suddividere il problema di diagnostica centralizzato in molteplici sotto-problemi distribuiti, dati in carico ad agenti detti Diagnostici Locali, che hanno una visione limitata del sistema, ma che possono comunicare con agenti vicini. In modo da sfruttare la natura distribuita dello schema proposto, gli agenti potranno cooperare sulla diagnostica di parti del sistema che siano comuni a più diagnostici, attraverso tecniche di consenso. Il Capitolo 2 introduce il problema della diagnostica basata su modello attraverso dei risultati recenti sulla diagnostica centralizzata di sistemi a tempo discreto con dinamica non lineare ed incerta. Lo sviluppo dell’architettura di diagnostica distribuita è trattato nel fondamentale Capitolo 3, mentre i Capitoli 4 e 5 mostrano come questa architettura distribuita è implementata a tempo discreto e a tempo continuo. In ogni capitolo è presente un esempio didattico, oltre a risultati analitici che caratterizzano le prestazioni ottenibili dall’architettura proposta.XX Ciclo197