volume | PIER Journals

Abstract

A multi-step deadbeat predictive control method for permanent magnet synchronous motors based on fuzzy adaptive particle swarm optimization (PSO) parameter identification is proposed to address the problem of performance degradation under parameter mismatch conditions. First, this method dynamically adjusts the learning factors of the PSO algorithm through fuzzy control, improving the convergence speed and stability of parameter identification. Secondly, this method can accurately identify key parameters such as stator resistance, inductance, and permanent magnet flux without the need for additional injection of excitation signals injections, effectively solving the problem of the under rank model under rank in traditional identification methods. The experimental results demonstrate that this method significantly improves the dynamic response speed and steady-state control accuracy of the system under parameter mismatch conditions, effectively suppresses speed fluctuations and current surges, improves current ripple characteristics, and provides a high-performance solution for high-precision driving scenarios such as CNC machine tools.

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Dr. Dazuo Zhou

Dr. Xin Wang