Time-varying command filters-based neural adaptive control with fixed-time prescribed performance for the PMSM with external disturbance and time delays

Abstract

This paper improves the design methodology of the permanent magnet synchronous motor (PMSM) controller by using different approaches. First, it introduces bounded time-varying filter gains. It integrates time-varying command filters into the controller design of PMSMs for the first time to optimize the system's filtering capability. Second, this paper presents a fixed-time asymmetric prescribed performance control (PPC) strategy to limit the output response of the PMSM to a specific asymmetric district and uses a prescribed time convergence function to raise the convergence speed. Finally, introducing disturbance observer (DOB) and Lyapunov-Krasovskii functions to compensate for external load disturbances and time delays improves the system's robustness. In summary, the novelties of this paper are to utilize these improvements to PMSM control, making the proposed time-varying command filters-based neural adaptive control (CFNAC) method closer to the practical situation.