Adaptive NN tracking control of uncertain nonlinear discrete-time systems with nonaffine dead-zone input.
IEEE T. Cybernetics(2015)
摘要
In the paper, an adaptive tracking control design is studied for a class of nonlinear discrete-time systems with dead-zone input. The considered systems are of the nonaffine pure-feedback form and the dead-zone input appears nonlinearly in the systems. The contributions of the paper are that: 1) it is for the first time to investigate the control problem for this class of discrete-time systems with dead-zone; 2) there are major difficulties for stabilizing such systems and in order to overcome the difficulties, the systems are transformed into an n-step-ahead predictor but nonaffine function is still existent; and 3) an adaptive compensative term is constructed to compensate for the parameters of the dead-zone. The neural networks are used to approximate the unknown functions in the transformed systems. Based on the Lyapunov theory, it is proven that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded and the tracking error converges to a small neighborhood of zero. Two simulation examples are provided to verify the effectiveness of the control approach in the paper.
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关键词
nonlinear control theory,uncertain systems,neural networks,dead-zone input,control system synthesis,nonaffine function,closed loop system,nonaffine pure-feedback form,nonlinear systems,n-step-ahead predictor,adaptive nn tracking control design,adaptive control,nonlinear discrete-time systems,lyapunov theory,adaptive compensative term,uncertain nonlinear discrete time systems,nonaffine dead-zone input,discrete time systems,adaptive nn control,closed loop systems,lyapunov methods,artificial neural networks,adaptive systems,vectors
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