Adaptive neural network control for a class of discrete-time nonlinear interconnected systems with unknown dead-zone |
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| Institution: | 1. School of Mathematics and Physics, Bohai University, Jinzhou 121013, China;2. College of Engineering, Bohai University, Jinzhou 121013, China;1. College of Information Sciences and Technology, Donghua University, Shanghai 200051, China;2. College of Computer Sciences and Technology, Donghua University, Shanghai 200051, China;1. College of Engineering, Bohai University, Liaoning, Jinzhou, China;2. Experiment Management Center, Bohai University, Liaoning, Jinzhou, China |
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| Abstract: | In this paper, the problem of adaptive neural network control design is addressed for a kind of discrete-time nonlinear interconnected systems with unknown dead-zone. The control purpose of this paper is to design an adaptive neural network controller to ensure the systems stability and achieve the desired control performance. The neural networks are utilized to approximate the unknown functions. On the basis of utility functions, the critic signals are considered in the designed control signals. In order to offset the impact of unknown asymmetric dead-zone in the controlled system, the adaptive assistant signal is constructed. Based on the gradient descent rule, the weight tuning laws are obtained. The difference Lyapunov function theory is adopted to prove the studied system stability. The viability of the devised control strategy is further testified via some simulation results. |
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