CAJ | 학술논문

为了提高无刷直流电机调速驱动系统的性能,提出神经网络自适应滑模变结构控制策略.推导无刷直流电机端电压与转速之间的微分方程,运用滑模变结构控制理论,通过调节端电压来实现转速控制;为了有效抑制系统在滑模切换面上的抖振采用自适应算法调整滑模增益的大小;从实际应用的角度出发,利用神经网络对非线性函数的任意精度拟合性,设计径向基函数神经网络估计器对控制量中广义扰动进行动态估计.仿真和实验结果表明采用本文提出的方法控制无刷直流电机,超调量小,速度响应快,控制精度高,且系统对各种干扰和参数摄振具有较强的鲁棒性,动、静态性能均优于PID控制.
위료제고무쇄직류전궤조속구동계통적성능,제출신경망락자괄응활모변결구공제책략.추도무쇄직류전궤단전압여전속지간적미분방정,운용활모변결구공제이론,통과조절단전압래실현전속공제;위료유효억제계통재활모절환면상적두진채용자괄응산법조정활모증익적대소;종실제응용적각도출발,이용신경망락대비선성함수적임의정도의합성,설계경향기함수신경망락고계기대공제량중엄의우동진행동태고계.방진화실험결과표명채용본문제출적방법공제무쇄직류전궤,초조량소,속도향응쾌,공제정도고,차계통대각충간우화삼수섭진구유교강적로봉성,동、정태성능균우우PID공제.
In this paper a novel neural adaptive sliding model variable structure control strategy is proposed to improve the perfor-mances of brushless DC speed systems. Firstly, a sliding model variable structure speed controller of BLDCM is designed according to its mathematical model, in which an adaptive algorithm for regulating the switching gain is adopted to restrain the chattering around the sliding plane. And then radial basis function neural network (RBFNN) is devised to estimate the generalized disturbance item of the control variable dynamically. Finally, some simulation and experimental results are provide to indicate that the speed sys-tem of BLDCM by using the proposed control method has less overshoot, quick velocity response, higher control precision and good robustness, which is insensitive to the parameter chattering and many disturbances.