Adaptive output feedback control of systems with unmodeled dynamics and output constraint. (Chinese. English summary) Zbl 1389.93156
Summary: An adaptive output feedback dynamic surface control scheme is proposed for a class of output feedback nonlinear systems with unmodeled dynamics and output constraint. The radial basis function neural networks are utilized to approximate unknown nonlinear continuous functions. The \(K\)-filters and dynamic signal are designed to estimate the unmeasured states and deal with the dynamic uncertainties, respectively. By introducing a Barrier Lyapunov Function (BLF) and designing the adaptive controller, the boundedness of the BLF and the output constraint can be guaranteed. By theoretical analysis, the closed-loop control system is shown to be semi-globally uniformly ultimately bounded, and satisfy the output constraint. Simulation results show the effectiveness of the proposed approach.
MSC:
93C40 | Adaptive control/observation systems |
93B52 | Feedback control |
92B20 | Neural networks for/in biological studies, artificial life and related topics |
93E10 | Estimation and detection in stochastic control theory |
93D30 | Lyapunov and storage functions |