Robust adaptive observer for nonlinear time-delay systems with disturbances and uncertainties

A method of designing robust adaptive observer for nonlinear continuous-time systems with time-delays is presented.It is assumed that the nonlinear functions of the system satisfy Lipschitz condition.The observer is derived considering plant disturbances,structured parameter uncertainties and unknown parameters.Like any other adaptive observer for nonlinear systems with ideal working conditions,it also simultaneously estimates both the states and unknown parameters.This property is very much useful for many applications like fault diagnosis.The convergence of the state errors and estimated unknown parameters are analysed by H_(∞)-control.The sufficient conditions for the existence of the observer are determined and expressed in linear matrix inequality form.With the help of a numerical example,the effectiveness of the proposed observer is demonstrated.

Adaptive unknown input observer approach for multi-fault diagnosis of PEM fuel cell system with time-delays

An adaptive unknown input observer(AUIO)for polymer electrolyte membrane fuel cell system with time-delays is developed and applied to formulate a fault diagnosis algorithm for multiple actuator fault detection and isolation(MAFDI).In a scheme based on multiple-model,a group of observers are developed based on a model that describes the system in the presence of a specific actuator fault.The observers are used to generate fault-dependant residual signals.When a model matches the system,the residual signal is zero and becomes non-zero in case of a faulty scenario.Two types of actuator faults are considered namely stuck fault,where the inputs delivered by the faulty actuators are blocked to constant value,and loss of effectiveness fault.The effectiveness of the proposed AUIO and MAFDI algorithm is shown with simulation results.