This paper studies the problem of adaptive fuzzy asymptotical quantized tracking control of non-strict-feedback systems with unmodeled dynamics. A dynamic signal is used to cope with the unmodeled dynamics and fuzzy systems are introduced to approximate the packaged unknown nonlinearities. Based on backstepping technique and fuzzy approximation property, a systemic fuzzy adaptive control scheme is proposed. By the utilization of Lyapunov theory, the semi-globally uniformly ultimate boundedness of all closed-loop system signals and asymptotical tracking performance are guaranteed. The main contributions of this work are two aspects: (i) a backstepping-based quantized control algorithm is firstly extended to nonlinear systems with unmodeled dynamics and non-strict-feedback structure; (ii) the semi-globally asymptotic tracking control scheme is independent of the quantized parameter. Simulation results verify the presented control approach.

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Keywords Adaptive fuzzy control, Input quantization, Non-strict-feedback systems, Unmodeled dynamics
Persistent URL dx.doi.org/10.1016/j.ins.2018.04.011
Journal Information Sciences
Citation
Wang, H. (Huanqing), Xiaoping Liu, P. (Peter), Xie, X. (Xuejun), Liu, P, Hayat, T. (Tasawar), & Alsaadi, F.E. (Fuad E.). (2018). Adaptive fuzzy asymptotical tracking control of nonlinear systems with unmodeled dynamics and quantized actuator. Information Sciences. doi:10.1016/j.ins.2018.04.011