陷波滤波器谐振抑制参数优化方法
|
摘要
针对伺服系统谐振抑制中,陷波滤波器的深度和宽度不合理而使谐振抑制不理想的问题,提出陷波滤波器谐振抑制参数优化方法。利用速度偏差的FFT变换得到谐振频谱图,以最大幅值处的频率确定陷波频率;在频谱图上以曲线任意点的幅值与最大幅值的比值确定深度参数,并且以所对应的频率与谐振频率的宽度确定宽度参数;为了保证参数的合理性,以滤波后谐振频率处的幅值为适应度,利用改进粒子群优化算法对陷波深度和宽度参数进行优化,避免因噪声干扰和负载变化而使陷波参数陷入局部最优。实验结果表明:该方法能在线分析机械谐振并且匹配最优参数,可以大幅度降低机械谐振。
In the resonant suppression of the servo system, unreasonable depth and width of the notch filter may lead to poor resonance suppression effect. In this paper, an optimization method of resonant suppression parameters of notch filters is proposed. The resonant spectrum is obtained by FFT transformation of velocity deviation, and the notch frequency is determined by the frequency at the maximum amplitude. The depth parameter is determined by the ratio of the amplitude at any point of the spectrum curve to the maximum amplitude, and the width parameter is determined by the width between the corresponding frequency and the resonant frequency. In order to ensure the rationality of the parameters, the amplitude at the resonant frequency after filtering is used as the fitness, and the notch depth and width parameters are optimized by the improved particle swarm optimization(PSO) algorithm. This method can avoid the parameters trapping into local optimum due to noise interference and load change. The experimental results show that this method can analyze the mechanical resonance and match the optimal parameters on-line and significantly reduce the mechanical resonance.
In the resonant suppression of the servo system, unreasonable depth and width of the notch filter may lead to poor resonance suppression effect. In this paper, an optimization method of resonant suppression parameters of notch filters is proposed. The resonant spectrum is obtained by FFT transformation of velocity deviation, and the notch frequency is determined by the frequency at the maximum amplitude. The depth parameter is determined by the ratio of the amplitude at any point of the spectrum curve to the maximum amplitude, and the width parameter is determined by the width between the corresponding frequency and the resonant frequency. In order to ensure the rationality of the parameters, the amplitude at the resonant frequency after filtering is used as the fitness, and the notch depth and width parameters are optimized by the improved particle swarm optimization(PSO) algorithm. This method can avoid the parameters trapping into local optimum due to noise interference and load change. The experimental results show that this method can analyze the mechanical resonance and match the optimal parameters on-line and significantly reduce the mechanical resonance.
引文
[1]杨明,王璨,徐殿国.基于轴矩限幅控制的机械谐振抑制技术[J].电机与控制学报,2015,19(4):58-64.
[2]WANG W,XU J,SHEN A.Detection and reduction of middle frequency resonance for industrial servo[C].International Conference on Information Science and Technology.IEEE,2012:153-160.
[3]王璨,杨明,徐殿国.基于PI控制的双惯量弹性系统机械谐振的抑制[J].电气传动,2015,45(1):49-53.
[4]杨明,郝亮,徐殿国.基于自适应陷波滤波器的在线机械谐振抑制[J].哈尔滨工业大学学报,2014,46(4):63-69.
[5]李娜,李世华.基于自适应IIR滤波器的伺服系统机械谐振抑制[C].第27届中国控制与决策会议,2015:3418-3423.
[6]李宗亚,罗欣,沈安文.基于陷波器参数自调整的伺服系统谐振抑制[J].计算技术与自动化,2013,32(4):7-11.
[7]KIM T I,BAHN W,YOON J M,et al.Online tuning method for notch filter depth in industrial servo systems[C].Chinese Control Conference,2016:9514-9518.
[8]LEE D H,LEE J H,AHN J W.Mechanical vibration reduction control of two-mass permanent magnet synchronous motor using adaptive notch filter with fast Fourier transform analysis[J].Iet Electric Power Applications,2012,6(7):455-461.
[9]KANG J,CHEN S,DI X.Online detection and suppression of mechanical resonance for servo system[C].Third International Conference on Intelligent Control and Information Processing.IEEE,2012:16-21.
[10]王秋生,杨浩,袁海文.基于粒子群优化的数字多频陷波滤波器设计[J].仪器仪表学报,2012,33(7):1661-1667.
[2]WANG W,XU J,SHEN A.Detection and reduction of middle frequency resonance for industrial servo[C].International Conference on Information Science and Technology.IEEE,2012:153-160.
[3]王璨,杨明,徐殿国.基于PI控制的双惯量弹性系统机械谐振的抑制[J].电气传动,2015,45(1):49-53.
[4]杨明,郝亮,徐殿国.基于自适应陷波滤波器的在线机械谐振抑制[J].哈尔滨工业大学学报,2014,46(4):63-69.
[5]李娜,李世华.基于自适应IIR滤波器的伺服系统机械谐振抑制[C].第27届中国控制与决策会议,2015:3418-3423.
[6]李宗亚,罗欣,沈安文.基于陷波器参数自调整的伺服系统谐振抑制[J].计算技术与自动化,2013,32(4):7-11.
[7]KIM T I,BAHN W,YOON J M,et al.Online tuning method for notch filter depth in industrial servo systems[C].Chinese Control Conference,2016:9514-9518.
[8]LEE D H,LEE J H,AHN J W.Mechanical vibration reduction control of two-mass permanent magnet synchronous motor using adaptive notch filter with fast Fourier transform analysis[J].Iet Electric Power Applications,2012,6(7):455-461.
[9]KANG J,CHEN S,DI X.Online detection and suppression of mechanical resonance for servo system[C].Third International Conference on Intelligent Control and Information Processing.IEEE,2012:16-21.
[10]王秋生,杨浩,袁海文.基于粒子群优化的数字多频陷波滤波器设计[J].仪器仪表学报,2012,33(7):1661-1667.