Adaptive Neural Quantized Control for a Class of MIMO Switched Nonlinear Systems With Asymmetric Actuator Dead-Zone

Direct Neural Network Adaptive Tracking Control for Uncertain Non-Strict Feedback Systems With Nonsymmetric Dead-Zone

“…Asusmption 1 [27,29]. The dead-zone outputs u(t) is assumed to be not available and the parameters b r and b l are assumed to be unknown constants, but their signs are known, i.e., b r > 0 and b l < 0.…”

“…Unknown dead-zone input as one of the nonlinearities often occurs in the process of the practical engineering , which is a source of instability and limitation of performance of systems. Recently, the investigations of input dead-zone has attracted a great deal of attention [25][26][27][28][29][30][31]. Decentralized control for large-scale systems with actuator faults and tracking control for switched stochastic actuator dead-zone systems were discussed in [25,26].…”

“…[27] studied the non-backstepping VUFC algorithm for pure-feedback form. Based on switched nonlinear systems, [28] [29] extended time-varying tan-type barrier Lyapunov function adaptive fuzzy control and adaptive neural quantized control for states constrained systems and MIMO asymmetric actuator systems. Adaptive neural control [30] and fuzzy decentralized control [31] were proposed for unknown control directions systems and strong interconnected nonlinear systems in unmodeled dynamics.…”

Adaptive fuzzy finite‐time quantized control for stochastic nonlinear systems with full state constraints

“…In Reference 28, the authors first solved the backstepping control problem of uncertain nonlinear systems with quantized input signal. Then many interesting quantized control methods are developed for uncertain nonlinear systems, such as the robust quantized control, 29‐31 the finite‐time quantized control, 32,33 the event‐trigger quantized control, 34,35 and so forth.…”

“…In addition, different from the nonlinear strict‐feedback systems, the unknown nonlinear functions in every subsystem of the nonlinear nonstrict‐feedback systems are composed of whole system states. If the traditional control methods in References 1‐32,33‐35 are applied to the nonlinear nonstrict‐feedback systems, the algebraic loop problem will be inevitable in the control process. Thus, it is more difficult and challenging to address the control problem of the nonlinear nonstrict‐feedback systems.…”