Nussbaum function based unified event-triggered asymptotic tracking control for uncertain interconnected nonlinear systems with or without state constraints

The study investigates Nussbaum function based adaptive decentralized asymptotic tracking control for a class of interconnected nonlinear systems with or without state constraints. First, to simultaneously deal with both constrained and unconstrained systems, a unified nonlinear transformation function is developed. Second, the Nussbaum gain technique is employed to address the challenge of unknown control direction. An adaptive decentralized controller is then designed using backstepping and neural network techniques. Third, to reduce communication resources an event-triggering mechanism based on system states and constraint boundaries is incorporated. Theoretical analysis shows that all signals in the closed-loop system remain bounded, while the tracking error asymptotically converges to zero. Additionally, the Zeno phenomenon is proven to be avoided. Finally, the effectiveness of the proposed approach is validated through a simulation example.