Adaptive Neural Dynamic Surface Output Feedback Control for Nonlinear Full States Constrained Systems

Abstract

In order to solve the control problem of uncertain nonlinear systems with state constraints, a dynamic surface output feedback control technology based on Radial Basis Function (RBF) neural networks state observer is proposed. The state observer is designed to estimate the unknown state of the systems by using the approximation characteristics of RBF neural networks, and to constrain the system state by using the Barrier Lyapunov Function (BLF). Based on the backstepping control, a first-order low-pass filter is introduced to design a dynamic surface control (DCS), which solves the "differential explosion" phenomenon that can easily occur in backstepping control. Finally, the stability of the closed-loop system which is confirmed by the Lyapunov method guarantees the semi-globally uniformly ultimately boundedness (SGUUB) of all the signals. The effectiveness of the methods that the boundedness of the tracking errors, the observer states and the controllers can be guaranteed, and good control performance could be achieved is shown by simulation results. INDEX TERMSDynamic surface control, full state constraints, nonlinear constrained systems, RBF neural networks, state observer.

Platoon of uncertain unmanned surface vehicle teams subject to stochastic environmental loads

“…Regardless of the proposed back-stepping approaches for nonlinear systems, we have to point out that one of the main drawbacks of the backstepping approach for both deterministic and stochastic nonlinear systems is called explosion of complexity which was resolved using dynamic surface control (DSC) method in Reference 30 for deterministic cases. In addition to deterministic types of nonlinear systems, 31,32 the DSC technique is widely used in stability analysis of different classes of stochastic nonlinear systems, such as in References 33-35. For example, the adaptive neural tracking control problem for a class of uncertain stochastic nonlinear systems with nonstrict-feedback form and prespecified tracking accuracy is studied using the DSC method in Reference 33.…”

Design of Adaptive Sliding Mode Controllers for Perturbed Nonlinear Systems with Partial Unmeasurable States and State Constraints

“…Therefore, lots of researches on state constraints have been developed based on establishing barrier Lyapunov functions due to its simplicity. When utiliz-ing a barrier Lyapunov function methodology [20][21][22][23][24][25][26][27][28][29][30][31][32][33][34], one needs to create a barrier Lyapunov function first, and then design the controller through the function such that not only the barrier Lyapunov function is bounded, but also the controlled system is stable.…”

“…In order to deal with unmeasurable states and state constraint problems, backstepping control which utilizing barrier Lyapunov function were proposed in [20][21][22][23][24][25][26] for perturbed nonlinear systems, these methods all achieved the property of UUB. Intelligent control schemes were also developed for solving unmeasurable states and state constraint problems, and they also achieved the property of UUB [27][28][29][30][31][32][33][34]. Although the aforementioned works [20][21][22][23][24][25][26][27][28][29][30][31][32][33][34] can handle the problems of unmeasurable states and state constraints at the same time, several disadvantages are found in these systems: I.…”

“…Intelligent control schemes were also developed for solving unmeasurable states and state constraint problems, and they also achieved the property of UUB [27][28][29][30][31][32][33][34]. Although the aforementioned works [20][21][22][23][24][25][26][27][28][29][30][31][32][33][34] can handle the problems of unmeasurable states and state constraints at the same time, several disadvantages are found in these systems: I. The dynamic equations with match or unmatched perturbations considered in [20][21][22][23][24][25][26][27][29][30][31][32][33][34] have to be in strict feedback form.…”

“…II. The methods proposed in [20][21][22][23][24][25][26][27][28][29][30][31][32][33][34] can only achieve the property of UUB. III.…”