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由于传统的PID控制器是建立在被控对象精确已知的情况下,通常难以满足多变量、非线性、强耦合的无离合器电动汽车表贴式永磁同步电机(PMSM)精确的速度跟踪控制和高动态响应的性能要求,所以提出一种基于RBF神经网络辨识的自校正PID控制器,以提高负载转矩波动下的PMSM速度自动跟踪能力。仿真和实验结果表明,该系统减小了速度调节的超调量,加快了系统的速度响应,实现了无离合器电动汽车精确的速度跟踪控制。
Because the traditional PID controller is based on accurately known controlled object, it is usually difficult to meet the precise speed tracking control of multivariable, nonlinear and strongly coupled clutchless surface-mount permanent magnet synchronous motor (PMSM) And high dynamic response performance requirements, a self-tuning PID controller based on RBF neural network identification is proposed to improve the PMSM speed automatic tracking ability under load torque fluctuation. The simulation and experimental results show that the system reduces the overshoot of the speed regulation, accelerates the speed response of the system, and realizes the accurate speed tracking control of the clutchless electric vehicle.