Intelligent Prescribed Performance Output Regulation of Nonlinear Strict-Feedback Systems

The robust intelligent control method is addressed to solve the output regulation problem of nonlinear strict- feedback systems with the output constraints. The intelligent back-stepping method is designed to control the strict- feedback systems, where neural networks are introduced to approximate the differential terms to avoid the expansion of complexity. To satisfy the output constraints, an initial-condition-independent prescribed performance control scheme is addressed. Through a time-varying initial-condition-independent barrier function, the prescribed steady-state performance and dynamic performance of the control system can be ensured even if the reference signals or the initial values of system states are changed. Finally, the simulations are implemented on the second order strict- feedback nonlinear system and the hemispherical resonant gyroscope control system to verify the accurate system tracking and the initial-condition-independent prescribed performance.