A novel modeling and controlling approach for high‐order nonlinear systems

Abstract

This paper proposes a completely data-driven control law for a class of high-order nonlinear systems based on their virtual characteristic models. With sampled-data techniques and estimation methods, a novel lower-order adaptive characteristic model is constructed to reduce the system complexities. Moreover, a corresponding sliding mode control law is designed, which can guarantee tracking errors of the resulting closed-loop system converging into a predefined bound in finite time. The practical examples are provided to illuminate the effectiveness of the proposed approaches.