Motor servo systems in practical applications often face input delay and inherent model uncertainties, posing significant challenges to control design. To enhance the tracking accuracy of motor servo systems with input delay, this paper proposes a novel neural network-based adaptive control method with prescribed performance guarantees. Firstly, a mathematical model of motor servo system incorporating input delay is established. Subsequently, as the core of the proposed control methodology, the auxiliary dynamic related to input delay is defined, neural network technique is employed to approximate both the unknown system dynamic and input delay-related quantity, while a barrier function integrating prescribed performance is introduced to generate designed error signals. Then the controller is systematically derived through this framework. Through Lyapunov stability analysis, the proposed controller is rigorously proven to compensate for input delay while achieving prescribed performance. Comparative experiments validate the effectiveness of the proposed control strategy.
Dong et al. (Thu,) studied this question.