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This paper proposes an observer based adaptive tracking control strategy for a class of uncertain nonlinear systems with delay in state as well as in input. Self recurrent wavelet neural network (SRWNN) is used to approximate the uncertainties present in the system as well as to identify and compensate the dynamic nonlinearities. The architecture of the SRWNN is a modified model of the wavelet neural...
In this work an adaptive tracking control strategy for a class of non affine delayed systems subjected to actuator saturation is proposed. Self recurrent wavelet neural network (SRWNN) is used to approximate the uncertainties present in the system as well as to identify and compensate the nonlinearities introduced in the system due to actuator saturation. By using suitable transformation the system...
This paper presents a wavelet based adaptive observer based control strategy for a class of uncertain multiple input multiple output (MIMO) delayed nonlinear systems subjected to actuator saturation. The time delay observer presented in this paper is the extension of observer design for SISO systems. The proposed wavelet adaptive observer performs the task of identification of unknown system dynamics...
This Paper investigates the mean to design the observer and observer based controllers for a class of delayed nonlinear systems with Lipschitz conditions and unknown dynamics subjected to input constraints. A new design approach of full order wavelet based adaptive observer is proposed. Wavelet neural networks (WNN), which are having superior learning capability in comparison to conventional neural...
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