Tracking control of PMSM systems with asymmetric output constraint and multiple delays by adaptive dynamic surface control

This paper proposes an integrated adaptive dynamic surface control scheme for permanent magnet synchronous motor systems subject to simultaneous asymmetric output constraint, unknown time delays, input delays, and an unknown external disturbance. Unlike existing studies that address these issues separately or partially, our approach unifies nonlinear transformation, Lyapunov-Krasovskii functions (LKFs), and compensated dynamic auxiliary signals within a backstepping framework, enabling coexistence in handling multiple practical constraints without structural redesign. Specifically, a nonlinear transformation function is proposed to convert a system model with asymmetric output constraint into an unconstrained one. By jointly designing dynamic auxiliary signals and exponential-type LKFs, input delays are compensated. When addressing time-delay systems, an exponential-type LKF is constructed using a decoupled design strategy, in contrast to standard LKFs that incorporate delayed state vectors directly. This approach enhances robustness against uncertain delayed couplings and simplifies the controller synthesis process. Additionally, radial basis function neural networks (RBFNNs) are used to approximate the unknown nonlinear functions, simplifying controller design. Furthermore, the first-order filters are adopted to solve the “explosion of complexity”. The system stability analysis indicates that all signals are ultimately bounded, and the tracking error narrows down to a small neighborhood of the origin. Finally, the experimental results show the effectiveness of the proposed controller.