Event‐Triggered Adaptive Tracking Control With Prescribed Performance of Uncertain Nonlinear Systems

Abstract

ABSTRACT This article studies the event‐triggered adaptive tracking control problem for uncertain nonlinear systems. First, an adjustable prescribed performance function is introduced to constrain the tracking error bound, thereby improving the system tracking performance. Next, by designing an error transformation function, the constrained tracking error is converted into an unconstrained variable. This variable is utilized to construct virtual control signals, which enhances their design flexibility. Then, a class of command filters is proposed to filter the virtual control signals. In this case, the repeated derivatives of the above signals are replaced by the filter outputs without the derivatives. This suppresses the potential chattering phenomenon caused by direct differentiation. A dynamic signal compensator is further introduced to enhance signal quality. Subsequently, a novel event‐triggered adaptive controller is designed by integrating the above components, achieving the desired tracking objectives. In addition, we prove that the proposed event‐triggered mechanism leads to a smaller number of triggered events compared with the existing results. Finally, the effectiveness of the approach is validated through a practical application example based on a one‐link manipulator with motor dynamics.