摘要
无刷直流电机因其操控简单,高效率等优点被广泛应用于航空航天领域。针对航空航天领域无刷直流电机位置环易受外界干扰和非线性时变的特点,建立了相应的数学模型。针对传统控制方式位置响应精度不高的问题,引入了一种基于自适应模糊滑模与自适应径向基神经网络(ARBF)滑模复合的电机控制方法。复合控制器采用双模同步控制,通过自适应模糊滑模控制对外界扰动进行补偿,自适应径向基神经网络控制对电机的参数摄动进行补偿。从理论上证明了复合控制器的收敛性。仿真结果表明:自适应模糊滑模与自适应径向基神经网络滑模复合控制器具有强鲁棒性、抗干扰能力强等优点,其响应时间在0.1s以内,且无超调量的产生。有效地提高了无刷直流电机位置环的控制精度。
Brushless DC motor(BLDCM)is widely used in aerospace field for its simple manipulation and high efficiency.Aiming at the problem that the position loop of brushless DC motor is susceptible to external disturbance and nonlinear time-varying characteristics in aerospace field,a corresponding mathematical model was set up.Aiming at the problem of low precision of position response in traditional control mode,a motor control method based on adaptive fuzzy sliding mode and adaptive radial basis function(ARBF)neural network sliding mode was introduced.The dual mode synchronous control was adopted in the composite controller,the compensation of external disturbances was realized through adaptive fuzzy sliding mode control,and adaptive radial basis function neural network control was used to compensate the parameter perturbation of the motor.The convergence of the composite controller was proved theoretically.The simulation results show that the composite controller of adaptive fuzzy sliding mode and adaptive radial basis function neural network sliding mode has strong robustness and strong anti-interference ability.The response time is within 0.1s,and no overshoot is generated.The control accuracy of the position loop of brushless DC motor is effectively improved.
作者
王献策
陈雄
柴金宝
冯恺鹏
WANG Xian-ce;CHEN Xiong;CHAI Jin-bao;FENG Kai-peng(School of Mechanical Engineering,Nanjing University of Science and Technology,Nanjing Jiangsu 210094,China)
出处
《计算机仿真》
北大核心
2020年第8期30-34,265,共6页
Computer Simulation
基金
国家自然科学基金资助项目(51606098)
江苏省自然科学基金资助项目(BK20140772)。
