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Event-based adaptive NN controller design for strict-feedback discrete-time nonlinear systems with input dead zone and saturation. (English) Zbl 1482.93399

Summary: In this paper, an event-based adaptive neural network controller design method is proposed for a type of uncertain strict-feedback discrete-time nonlinear systems. This system contains uncertain functions and has input nonlinearities in the form of saturation and non-symmetric dead zone. Both event-triggered policy and adaptive law are considered. Radial basis function neural networks are employed to accomplish function approximation. Input dead zone and saturation are estimated by a summation of a known affine function and a bounded unknown function. A stabilising controller and adaptive law are designed via backstepping. The stability of the controlled systems is elaborated via the difference Lyapunov analysis method. Simulation results are given to verify the effectiveness of the proposed design scheme.

MSC:

93C65 Discrete event control/observation systems
93C40 Adaptive control/observation systems
93B52 Feedback control
93C55 Discrete-time control/observation systems
93C10 Nonlinear systems in control theory
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