Nonlinear Observer-Based Fault Detection

This communication deals with the problem of designing a nonlinear observer in order to achieve fault detection and localization for a wide class of nonlinear systems subjected to bounded nonlinearities. A dedicated nonlinear observer scheme (DNOS) for fault detection and identification in reconstructible systems is proposed. INTRODUCTION State observation of nonlinear dynamical systems is becoming a growing topic of investigation in the specialized literature. The reconstruction of the time behaviour of state variables remains a major problem both in control theory and process diagnosis. Researchers attention is being particularly focused on the design of adaptive observers for on-line process state estimation. There is increasing awareness that to ensure robustness in performance requires simpler and stable adaptive observer schemes. Linear systems have received considerable attention (Luenberger, 1966), (O'Reilly, 1983) leading to several stable adaptive observer systems (Kreisselm..

Observability Analysis And Sensor Placement

. The quality of the state estimation of a system is strongly conditioned by the number of measurements obtained from this system. Here, this dependence is studied by specifying especially the influence of the number and the position of sensors as well as of their precision. When some variables are necessary for the control, the possibility of failure of some sensors is analysed from the calculation of the whole system reliability. The reciprocal problem is also presented: what is the measurement system allowing to respect some constraints on the observability, the redundancy and the reliability. Key Words. Sensor placement; observability; redundancy; reliability; control system design; sensor failures; measurement system 1. INTRODUCTION Nowadays, the conception of a measurement system is of fundamental importance. Indeed, the position of sensors and their number condition the possibility to observe a process, to estimate its state and consequently to determine the type of control to..

Identification of Fuzzy Models

The objective of this work is to describe a numerical technique to identify parameters of a fuzzy model. When this model and the membership functions of the input variables are continuously differentiable, we show that the estimation of parameters can be performed with a two-levels hierarchical algorithm, comprising the estimation of the model parameters and the estimation of the membership functions parameters. The proposed algorithm is then applied to an example describing a non-linear system. KEYWORDS Fuzzy model, identification, parameter estimation. 1. INTRODUCTION Building of fuzzy models can be applied to fuzzy control and to modeling of complex systems. Moreover, the implementation of a fuzzy logic controller involves the design of linguistic rules to compute the command to be applied on a process according to the measurement of the position error. In simple situations, these rules can be derived from those of a conventional PID controller ; on the other hand, for non-linear ..

Some Ideas About The Design Of Measurement Systems

The quality of the state estimation of a system and, consequently, its dependability are strongly conditioned by the number and the location of the measurements. The availability of a system may be increased if this latter is able to function even in the presence of sensor breakdowns. So, the measurement planning (measurement system design) represent a very important stage. This communication presents a method for assessing the availability of the necessary information for the process control and defining the sensor locations such that the variables required for controlling the process remain always observable even if one or more sensors become defective. Underlying, the connections between several concepts such observability, redundancy, sensor location and reliability are emphasised. 1 Introduction Monitoring a process requires a certain number of measurements which are usually supplied by sensors; unfortunately, some of these sensors may breakdown and the corresponding measurements..