Showing papers by "José Ragot published in 1996"

Design of observers for descriptor systems affected by unknown inputs

Abstract: A simple and direct procedure for designing unknown input observers for continuous descriptor systems is presented. The design of a state observer is investigated and an extension to estimate a linear function of the state and input is proposed. The chosen approach is based on the transformation of the system state space representation into particular design coordinates via a generalized matrix inversion technique. Assuming that the measurement matrix is full line rank involves many calculation simplifications. Special emphasis on the computational aspect of the observer matrices is provided. An illustrative example is also included.

Observers and redundancy equations generation for systems with unknown inputs

Abstract: In order to detect sensor and actuator failures or process disturbances, we use analytical redundancy in order to generate a variable that might contain information about the defects. This variable, also called a residual, is excepted to be significant of the defects as it is computed such that its value is equal to zero when no failure occurs and quite different from it otherwise. Several ways to generate the residuals have been developed but we specially study two techniques. The first one is a direct residual generation based on the parity space approach whereas the second one is based on an output estimation of the implied process which is further compared to its measure to create the residual. This paper describes a procedure for the residual generation using an observer in both cases of known and unknown input systems. Moreover; we show that direct redundancy, i.e. the input-output system transfer function, is not only useful to generate the residual but also provides a signal linked with one generated by the previous observer. Our results are put into theorem and lemma format.

About the design of measurement systems and fault accommodation

Abstract: The quality of the state estimation of a system and, consequently, its dependability are strongly conditioned by the number and the location of the sensors. 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) represents 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.

State equations and decomposition into Laguerre functions

Abstract: For a linear system, one establishes a connection between the coefficients of the decomposition into Laguerre functions of the inputs and the outputs of the system. When the system is modelled by a state equation, it is showed that the two series are related through a state equation whose matrices are depending of those of the state equations of the system. The new state representation may be used for analysing linear dynamic systems.

Model simplification and system approximation with constrained Laguerre models

Abstract: A functional approximation method is presented based on Laguerre functions. This paper illustrates the use of supplementary time constraints (e.g., interpolation of the value of the impulse response of a system at a given time) and frequency constraints (e.g., interpolation of the value of the system's transfer function at a given frequency) in order to improve the quality of approximation. The proposed method may be employed either in the reduction of a known system or in the identification of an unknown system. A number of numerical results further clearly show its advantage over unconstrained least squares approximations.