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对基于全阶状态观测器的异步电机矢量控制系统进行了研究与改进。通过对系统数学模型的深入分析,将改进的重心聚焦在全阶状态观测器反馈增益系数的优化上。以粒子群算法(Particle Swarm Optimization,PSO)作为优化手段,实现反馈增益系数的自寻优。在此基础上,论文通过对粒子速度更新公式的改进,使算法收敛速度明显提高。在Matlab/Simulink仿真环境下,进行了仿真验证。结果表明,基于改进型粒子群算法全阶状态观测器的异步电机矢量控制系统具有更加准确的转速估算精度与良好的运行性能。
The induction motor vector control system based on full order state observer is studied and improved. Through in-depth analysis of the mathematical model of the system, the improved center of gravity is focused on the optimization of the feedback gain coefficient of the full order state observer. Particle swarm optimization (Particle Swarm Optimization, PSO) is used as an optimization method to realize self-optimization of feedback gain coefficient. On this basis, through the improvement of particle velocity update formula, the convergence speed of the algorithm is obviously improved. In Matlab / Simulink simulation environment, the simulation verification. The results show that the induction motor vector control system based on the improved state-of-the-art particle swarm optimizer has a more accurate speed estimation accuracy and good running performance.