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A nonlinear multivariable adaptive decoupling PID control strategy based on multiple models and neural network is proposed for a class of uncertain discrete time nonlinear dynamical systems. The adaptive decoupling PID controller is composed of a linear adaptive PID decoupling controller, a neural network nonlinear adaptive PID decoupling controller and a switch mechanism. The PID parameters of such...
In this paper a new approach to the design of multivariable adaptive-fuzzy controllers is proposed. The approach is based on fuzzy Lyapunov synthesis, that is an extension of the classical Lyapunov synthesis in the domain of computing with words. The closed-loop system is monitored and the parameters of the controller are adapted in order to minimizing the error between the actual and the desired...
A new adaptive nonlinear state predictor (ANSP) is presented for a class of nonlinear systems with input time-delay. High-order neural network (HONN) incorporating with a special identification model is first employed to identify the unknown nonlinear time-delay system. The predicted weight updating law of neural network is calculated based on the identification, which can be used to predict the future...
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