基于预测模型双模糊分数阶PID的BLDCM调速系统优化控制

无刷直流电机（BLDCM）具有复杂的非线性系统，强耦合、变量多等特点，传统的PID控制无法获得满意的控制效果。为此，在模糊控制、分数阶微积分及模型预测相关理论的基础上，提出了预测模型双模糊分数阶PID控制器。分数阶控制为系统提供更多的控制余度，并采用一种间接算法（Oustaloup算法）完成整数阶PID控制的延伸和扩展，模糊控制实现分数阶PID控制参数的在线调整；建立预测模型，并引入模糊控制动态调整预测模型系数K值，实现更加精确的控制。针对模糊分数阶PID控制器中参数选择，又提出了一种改进的万有引力算法进行参数优化，增强控制器的自适应能力。仿真结果表明:基于改进万有引力算法的预测模型双模糊分数阶PID控制的BLDCM调速系统较传统的PID控制具有更快的响应速度、更小的超调量及抗负载扰动能力强等优良的动、静态性能指标。

Optimal control of BLDCM speed control system based on predictive model of dual fuzzy fractional PID

BLDCM (BLDCM) has the characteristics of complex nonlinear system, strong coupling and many variables, so the traditional PID control can not achieve satisfactory control effect.Based on the theory of fuzzy control, fractional calculus and model prediction, a dual fuzzy fractional PID controller is proposed. Fractional order control provides more control redundancy for the system, and uses an indirect algorithm (oustaloup algorithm) to complete the extension and expansion of integer order PID control, and fuzzy control realizes the on-line adjustment of Fractional Order PID control parameters; establishes the prediction model, and introduces fuzzy control to dynamically adjust the prediction model coefficient K value to achieve more accurate control. Aiming at the parameter selection of fuzzy Fractional Order PID controller, an improved universal gravitation algorithm is proposed to optimize the parameters and enhance the adaptive ability of the controller.The simulation results show that the BLDCM speed control system based on the improved universal gravitation algorithm has better dynamic and static performance indexes, such as faster response speed, smaller overshoot and strong anti load disturbance ability than the traditional PID control.