Decentralised adaptive tracking control for the interconnected nonlinear systems with asymmetric full state dynamic constraints

This paper studies the decentralised adaptive tracking control problem for the interconnected nonlinear systems with asymmetric full state dynamic constraints and input quantisation using dynamic event triggering mechanism. The broad learning system (BLS) is firstly utilised to identify the unstructured uncertainties, and a BLS-based nonlinear observer is established to estimate the unmeasurable states. Then, a unified barrier function (UBF) is constructed to address the asymmetric full state dynamic constraints. Next, both of command-filtered backstepping control technique and dynamic event triggering mechanism are adopted to design the control scheme in the asymmetric full state dynamic constraints case. The proposed control scheme could guarantee that all signals of the closed-loop systems are semi-globally ultimately uniformly bounded (SGUUB), the tracking errors converge to the bounded compact set and the full states dynamic constraints are not violated. Finally, a simulation example is given to illustrate the effectiveness of the proposed control scheme.