Marcel Staroswiecki

Fault Accommodation for Nonlinear Dynamic Systems

This note investigates process fault accommodation in a class of nonlinear continuous-time systems. A new fault estimation module, based on an adaptive estimator, is first proposed. The fault tolerant controller is constructed to compensate for the effect of the faults by stabilizing the closed-loop system. A flexible joint robotic example is given to illustrate the efficiency of the proposed approach

Optimal design of fault tolerant sensor networks

The selection of measurements is one of the most important problems in the design of process instrumentation. This paper deals with the design of sensor networks such that the observability of the variables, which are necessary for the process control, remains satisfied in the presence of sensor failures. Pseudo-minimal and minimal sensor sets are organized into an oriented graph which contains all the possible reconfiguration paths for which those variables remain observable. A bottom-up analysis of this graph allows one to compute reliability functions which evaluate the robustness of the observability property with respect to sensor failures. The design of optimal sensor networks thus resumes to finding pseudo-minimal sensor sets such that the mean time before losing the observability property is larger than a pre-defined value.

What is Fault-tolerant Control

Abstract Faults in automated processes will often cause undesired reactions and shut-down of a controlled plant, and the consequences could be damage to the plant, to personnel or the environment. Fault-tolerant control is the synonym for a set of recent techniques that were developed to increase plant availability and reduce the risk of safety hazards. Its aim is to prevent that simple faults develop into serious failure. Fault-tolerant control merges several disciplines to achieve this goal, including on-line fault diagnosis, automatic condition assessment and calculation of remedial actions when a fault is detected. The envelope of the possible remedial actions is wide. This paper introduces tools to analyze and explore structure and other fundamental properties of an automated system such that any redundancy in the process can be fully utilized to enhance safety and availability.

Dynamic Output Feedback-Fault Tolerant Controller Design for Takagi–Sugeno Fuzzy Systems With Actuator Faults

This paper addresses the problem of robust fault estimation and fault tolerant control (FTC) for Takagi-Sugeno (T-S) fuzzy systems. A fuzzy-augmented fault estimation observer (AFEO) design is proposed to achieve fault estimation of T-S models with actuator faults. Furthermore, based on the information of online fault estimation, an observer-based dynamic output feedback-fault tolerant controller (DOFFTC) is designed to compensate for the effect of faults by stabilizing the closed-loop system. Sufficient conditions for the existence of both AFEO and DOFFTC are given in terms of linear matrix inequalities. Simulation results of an inverted pendulum system are presented to illustrate the effectiveness of the proposed method.

Diagnostic bond graphs for online fault detection and isolation

Abstract Analytical redundancy relations (ARR) are symbolic equations representing constraints between different known process variables (parameters, measurements and sources). ARR are obtained from the behavioural model of the system through different procedures of elimination of unknown variables. Numerical evaluation of each ARR is called a residual, which is used in model based fault detection and isolation (FDI) algorithms. For processes and systems with complex non-linearity, eliminating all unknown variables is not trivial, e.g. in the presence of algebraic loops, implicit equations, non-invertible functions, etc. However, most symbolically non-resolvable relationships can be numerically solved; and then, it becomes possible to maximise the number of structurally independent residuals. Bond graph modelling is used in this paper to derive ARR and to obtain the computational model in the case of non-resolvability of equations. A set of sub-graph substitutions in the bond graph model are developed. These substitutions directly lead to a form, where known variables (measurements, sources and parameters) are the inputs and the residuals are the outputs. Such a model is then called a diagnostic bond graph (DBG) model. It is shown that DBG models can be used for online residual computation as well as for offline verification using process data from a database. A method for the coupling of the bond graph model, used to generate the residuals, with a bond graph model, used to describe the process behaviour, is presented. The coupled model allows simulation of process behaviour both in the presence and in the absence of the faults, which is consequently used to obtain residual responses and validate the fault signatures.

Brief paper: Supervisory fault tolerant control for a class of uncertain nonlinear systems

This paper focuses on the design of a unique scheme that simultaneously performs fault isolation and fault tolerant control for a class of uncertain nonlinear systems with faults ranging over a finite cover. The proposed framework relies on a supervisory switching among a family of pre-computed candidate controllers without any additional model or filter. The states are ensured to be bounded during the switching delay, which ends when the correct stabilizing controller has been selected. Simulation results about a flexible joint robotic example illustrate the efficiency of the proposed method.

Fault tolerant cooperative control for a class of nonlinear multi-agent systems☆

Abstract This paper studies the target aggregation problem for a class of nonlinear multi-agent systems with the time varying interconnection topology. The general neighboring rule-based linear cooperative protocol is developed and a sufficient aggregation condition is derived. Moreover, it is shown that in the presence of agent faults, the target point is still reached by adjusting some weights of the cooperative protocol without changing the structure of the topology. An unmanned aerial vehicle team example illustrates the efficiency of the proposed approach.

Brief paper: Progressive accommodation of parametric faults in linear quadratic control

In this paper, a strategy based on the linear quadratic design, which progressively accommodates the feedback control law, is proposed. It significantly reduces the loss of performance that results from the time delay needed by fault accommodation algorithms to provide a solution. An aircraft example is given to illustrate the efficiency of progressive accommodation.

ON RECONFIGURABILITY WITH RESPECT TO ACTUATOR FAILURES

Abstract This papers considers the problem of fault tolerance with respect to actuator failures. Accommodation and reconfiguration strategies are presented, and the system reconfigurability is analysed under possible energy limitation constraints.

Adaptive observer design for robust fault estimation

In this article, fault diagnosis for a class of linear systems based on adaptive observer is investigated. Linear systems without model uncertainty are first considered, and two adaptive observers are designed for fault identification. The first one uses optimal design for minimizing the estimation error. The second one can achieve asymptotic fault estimation. The general situation where the system is subjected to either model errors or external disturbance is then discussed. Robust adaptive control techniques are applied to guarantee the convergence to a bounded set. Simulation of sensor fault diagnosis for an induction motor is presented to verify the effectiveness of the proposed method.