悬浮控制中的信号滤波算法研究
摘要
低速磁浮列车的悬浮系统是一个典型的非线性开环不稳定系统,由于电磁环境的复杂性和运行状态参数的不确定性,滤波降噪算法一直是悬浮控制的技术难点。本文围绕滤波算法在悬浮控制中的对比应用展开研究,采用理论分析与仿真实验相结合的方法,主要完成了以下工作:
首先,建立了单点悬浮系统的数学模型,研究了电流环和位置环的设计问题,并通过时域和频域工具相结合的方法分析了控制系统各个参数对悬浮系统稳定性的影响。另外,通过实验方法建立了悬浮系统的噪声模型,并用功率谱密度描述噪声的频率特性。
其次,分析了系统中常规的几种低通滤波器对系统抗干扰能力的性能情况,分析了陷波器在抑制窄带宽交流噪声方面的应用效果。此外,从系统的稳定性角度分析了低通滤波器和陷波器对系统稳定性的影响。
然后,针对悬浮系统中存在的噪声特点采用了卡尔曼滤波方法。对卡尔曼滤波器在悬浮控制系统中的应用做了理论分析和仿真实验。仿真实验表明悬浮控制系统采用卡尔曼滤波器后能够有效地减小噪声带来的影响、提高鲁棒性。
最后,将最小二乘自适应滤波器应用到悬浮控制系统以抑制系统噪声,并通过递推最小二乘算法以减少程序的运算量。仿真实验表明该滤波器对噪声具有良好的抑制作用。
通过对上述几种滤波算法的分析比较,提出了适合于磁浮列车实际运行需要的滤波算法,对悬浮控制算法的设计提供了重要的参考。
The suspension system of the low-speed maglev train is a typical non-linear open-loop unstable system, and research on filtering and noise-reducing algorithms is a key technology in suspension control because of the complicacy of the electromagnetic environment and the uncertainties of the operational state parameters. This dissertation concentrates on the comparison of the application of different filtering algorithms in the suspension control system, using theoretical analysis as well as simulations and experiments. The main jobs are listed as follows:
Firstly, a dynamic model of a single electro-magnet suspension system is established, and a current loop and a position control loop are designed. Analyses of the impacts to the stability of the whole system due to control parameters are undertaken in both the time domain and the frequency domain, and the noise model of the suspension system is introduced. Moreover, a model is estabilished in the experimental way to discribe the nosie of the suspension system, and the Power Spectral Density (PSD) is employed to describe the frequency characteristics of the noise.
Secondly, the anti-interference performance of several low-pass filters in common use is explored, and the performance of the notch filter in suppressing the nerrow-band alternating-current noise is dicussed. In addition, the influences of the low-pass filter and the notch filter on the stability of the suspension control system are also analyzed.
Thirdly, considerring the characteristics of the noise in the suspension control system, the Kalman filter is used. Theoretical analysis and simulation validation have been undertaken on the application of the Kalman Filter in the suspension control system. The simulation result indicates that using the Kalman filter, the suspension control system can significantly reduce the impact of the noise and its robustness is therefore improved.
Finally, the Least Squares (LS) adaptive filter is applied to the suspension control system to suppress the noise, and the Recursive Least Squares (RLS) algorithm is applied to reduce the computational complicacy. Simulation shows that the adaptive filter performs well in suppressing the noise.
According to the analysis and comparison of the algorithms listed above, filtering algorithm which meets the requirements of the maglev train is proposed, which provides a significant referrence for the suspension control algorithm.
首先,建立了单点悬浮系统的数学模型,研究了电流环和位置环的设计问题,并通过时域和频域工具相结合的方法分析了控制系统各个参数对悬浮系统稳定性的影响。另外,通过实验方法建立了悬浮系统的噪声模型,并用功率谱密度描述噪声的频率特性。
其次,分析了系统中常规的几种低通滤波器对系统抗干扰能力的性能情况,分析了陷波器在抑制窄带宽交流噪声方面的应用效果。此外,从系统的稳定性角度分析了低通滤波器和陷波器对系统稳定性的影响。
然后,针对悬浮系统中存在的噪声特点采用了卡尔曼滤波方法。对卡尔曼滤波器在悬浮控制系统中的应用做了理论分析和仿真实验。仿真实验表明悬浮控制系统采用卡尔曼滤波器后能够有效地减小噪声带来的影响、提高鲁棒性。
最后,将最小二乘自适应滤波器应用到悬浮控制系统以抑制系统噪声,并通过递推最小二乘算法以减少程序的运算量。仿真实验表明该滤波器对噪声具有良好的抑制作用。
通过对上述几种滤波算法的分析比较,提出了适合于磁浮列车实际运行需要的滤波算法,对悬浮控制算法的设计提供了重要的参考。
The suspension system of the low-speed maglev train is a typical non-linear open-loop unstable system, and research on filtering and noise-reducing algorithms is a key technology in suspension control because of the complicacy of the electromagnetic environment and the uncertainties of the operational state parameters. This dissertation concentrates on the comparison of the application of different filtering algorithms in the suspension control system, using theoretical analysis as well as simulations and experiments. The main jobs are listed as follows:
Firstly, a dynamic model of a single electro-magnet suspension system is established, and a current loop and a position control loop are designed. Analyses of the impacts to the stability of the whole system due to control parameters are undertaken in both the time domain and the frequency domain, and the noise model of the suspension system is introduced. Moreover, a model is estabilished in the experimental way to discribe the nosie of the suspension system, and the Power Spectral Density (PSD) is employed to describe the frequency characteristics of the noise.
Secondly, the anti-interference performance of several low-pass filters in common use is explored, and the performance of the notch filter in suppressing the nerrow-band alternating-current noise is dicussed. In addition, the influences of the low-pass filter and the notch filter on the stability of the suspension control system are also analyzed.
Thirdly, considerring the characteristics of the noise in the suspension control system, the Kalman filter is used. Theoretical analysis and simulation validation have been undertaken on the application of the Kalman Filter in the suspension control system. The simulation result indicates that using the Kalman filter, the suspension control system can significantly reduce the impact of the noise and its robustness is therefore improved.
Finally, the Least Squares (LS) adaptive filter is applied to the suspension control system to suppress the noise, and the Recursive Least Squares (RLS) algorithm is applied to reduce the computational complicacy. Simulation shows that the adaptive filter performs well in suppressing the noise.
According to the analysis and comparison of the algorithms listed above, filtering algorithm which meets the requirements of the maglev train is proposed, which provides a significant referrence for the suspension control algorithm.
引文
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