Predictor-Based Fuzzy Tracking Control for Nonlinear Systems: A Reference-Independent Output Constrained Approach

In this paper, a predictor-based fuzzy safety control framework is proposed for uncertain nonlinear systems with reference-independent output constraints. A safety-compliant reference regulation mechanism is developed to reshape potentially infeasible references into safety reference signals, thereby eliminating the conventional admissible-reference assumption. A novel dual-constraint framework is developed to simultaneously enforce output constraints and prescribed performance in a unified manner, allowing explicit boundary construction without undesirable coupling. To handle uncertainty, a predictor-based simplified fuzzy approximator is constructed, in which prediction errors rather than tracking errors are employed to update the norm of weight vector, substantially reducing computation complexity and alleviating transient chattering. Meanwhile, the use of prediction errors also decouples control and estimation loops, thereby simplifying the stability analysis. Furthermore, a new transient analysis theorem is established to quantify chattering degree and explicitly reveal the influence of design parameters. Rigorous Lyapunov-based analysis proves that all closed-loop signals remain bounded, and both safety and performance constraints can be strictly satisfied. Simulation results validate the usefulness and superiority the proposed method.