Robust Discrete‐Time Prescribed Performance Control With Adaptive Switchable Structure for Unknown Dynamics and Disturbances

ABSTRACT This paper presents a prescribed performance control (PPC) framework for discrete‐time systems to regulate tracking errors under abrupt disturbances and nonlinearities, such as dead‐zone effects. The proposed approach addresses two scenarios: when the error remains within prescribed boundaries and when it exceeds the funnel boundary. A multi‐input fuzzy rules emulated network (MiFREN) is integrated for adaptive compensation, while a switching mechanism and adaptive learning law enhance robustness, even when the tracking error approaches or exceeds the boundary. Theoretical analysis establishes closed‐loop stability and performance guarantees under practical parameter selection conditions. Experimental validation on a DC‐motor torque control system demonstrates the effectiveness of the proposed approach. The method not only eliminates singularities but also significantly reduces control effort variations, especially when subjected to disturbances.