Robust estimation-free decentralized prescribed performance control of nonaffine nonlinear large-scale systems

In this paper, a low-complexity robust estimation-free decentralized prescribed performance control scheme is proposed and analyzed for nonaffine nonlinear large-scale systems in the presence of unknown nonlinearity and external disturbance. To tackle the high-order dynamics of each tracking error subsystem, a time-varying stable manifold involving the output tracking error and its high-order derivatives is constructed, which is strictly evolved within the envelope of user-specialized prescribed performance. Sequentially, a robust decentralized controller is devised for each manifold, under which the output tracking error and its high-order derivatives are proven to converge asymptotically to a small residual domain with prescribed fast convergence rate. Additionally, no specialized approximation technique, adaptive scheme, and disturbance observer are needed, which alleviates the complexity and difficulty of robust decentralized controller design dramatically. Finally, 3 groups of illustrative examples are used to validate the effectiveness of the proposed low-complexity robust decentralized control scheme for uncertain nonaffine nonlinear large-scale systems.