Command filter-based adaptive event-triggered control for switched nonlinear systems with full state constraints. (English) Zbl 1533.93821
Summary: An adaptive event-triggered control issue based on command filter and dynamic surface control is studied for switched nonlinear systems with full state time-varying constraints in this article. To handle state constraints, the nonlinear mapping conversion technique is used. Radial basis function neural networks (RBFNNs) are utilized to approximate unknown nonlinear continuous functions. Adaptive control algorithm is designed based on command filtered backstepping technology. Novel even triggered control is constructed for two different cases in the switching interval. Furthermore, all signals in the switched system are proved to be semi-globally uniformly ultimate bounded (SGUUB) by the aid of dynamic surface control method under arbitrary switching. Meanwhile, all states do not violate the preset constraints and Zeno phenomenon is avoided. The validity of the presented approach is confirmed through a numerical simulation result.
© 2023 John Wiley & Sons Ltd.
© 2023 John Wiley & Sons Ltd.
MSC:
| 93E11 | Filtering in stochastic control theory |
| 93C40 | Adaptive control/observation systems |
| 93C65 | Discrete event control/observation systems |
| 93C30 | Control/observation systems governed by functional relations other than differential equations (such as hybrid and switching systems) |
| 93C10 | Nonlinear systems in control theory |
Keywords:
command filter; dynamic surface control; event-triggered control; full state constraints; strict-feedback switched nonlinear systemsReferences:
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