Adaptive neural tracking control for nonstrict‐feedback nonlinear systems with unknown backlash‐like hysteresis and unknown control directions

Abstract

Summary In this paper, a neural network–based adaptive tracking control problem is investigated for a class of nonstrict‐feedback nonlinear systems in the presence of unknown backlash‐like hysteresis nonlinearity, unmodeled dynamics, and unknown control directions. A state feedback controller is developed for the considered system by applying the adaptive backstepping technique and neural networks. The design difficulties exhibited in this paper due to unmodeled dynamics, unknown control directions, and nonstrict‐feedback form are handled by resorting to a dynamic signal, a Nussbaum function, and the variable separation approach, respectively. It is shown that the designed adaptive controller can guarantee that all the signals remain bounded and that the desired signal can be tracked with a small domain of the origin. A numerical example and an example of a real plant for a one‐link manipulator are provided to show the feasibility of the newly designed controller scheme.

Integral barrier Lyapunov function‐based adaptive fuzzy output feedback control for nonlinear delayed systems with time‐varying full‐state constraints

“…Along with (12), (14), and (15), the time derivative of V e iṡ V e =̇e T Pe + e T Ṗe = −e T Qe + 2e T P…”

“…Meanwhile, the time-varying state constraint problems and input saturation are simultaneously considered compared with the existing nonstrict-feedback control results. 11,12 Especially the problem that the selection range of the initial value in References 32-36 is small has been solved. In addition, we also address the issue of "explosion of complexity" existing in References 32-36.…”

Finite‐time adaptive control of high‐order nonlinear systems with unknown control coefficients and actuator fault

“…2,27 Particularly, when the system has external disturbances, it was just guaranteed that all the signals in the closed-loop system were bounded. [28][29][30] Consequently, the finite-time control problem cannot be solved under the Nussbaum-gain functions. Although the finite-time control problem has been considered in References 31,32, the bounds of the control coefficients were assumed to be known.…”

“…And different from the previous results, [23][24][25]31,32,[37][38][39] we do not require a priori knowledge of the uncertainties including the unknown control coefficients, uncontrollable actuation fault, and the disturbance. 2Compared with the existing results 2,[27][28][29][30] where Nussbaum function was utilized to deal with the unknown control coefficients, a different and novel switching-type controller is proposed in our article. By regulating the controller parameter online through the switching mechanism, the uncertainties, which exist in the nonlinear functions and input, can be compensated.…”

“…The first difficulty arises from the unknown control coefficients. As we all known, the unknown control directions were always dealt with by utilizing the Nussbaum‐gain functions at present, see References 2,27‐30 and references therein. However, the system states can just asymptotically converge to zero under the Nussbaum‐gain functions 2,27 .…”