Adaptive decentralized control for large-scale nonlinear systems with finite-time output constraints by multi- dimensional Taylor network

This paper investigates the adaptive decentralized control problem for a class of large-scale nonlinear systems with finite-time output constraints. In order to ensure that the tracking errors are constrained within a predefined boundary in finite time, a novel adaptive barrier Lyapunov function (BLF) control method is proposed by combining the modified finite-time performance function (FTPF) in the first step of backstepping process. Besides, the mean value theorem and regulating functions are employed to handle the difficulties caused by interconnection functions in large-scale systems. Subsequently, with the approximation performance of multi-dimensional Taylor network (MTN), a MTN-based adaptive decentralized tracking control scheme is developed to guarantee that the tracking errors satisfy the prescribed performance and all signals of the closed-loop systems are bounded. Finally, the stability theory analysis and simulation results demonstrate the effectiveness of the proposed method.