基于TS模糊推理和李亚普诺夫理论的有源电力滤波器控制

Takagi-Sugeno Fuzzy Control and Lyapunov-Function Based Stability Control of Active Power Filter

针对负载和参数变化带来的有源电力滤波器(activepower filter,APF)精确数学模型难以获得以及系统稳定性问题,分别在APF的直流电压控制中引入TS型模糊控制器,在电流控制中引入基于李亚普诺夫稳定性理论的控制方法,保证了APF的控制精度和稳定性。首先通过对直流侧电压误差和误差变化率进行TS模糊控制得到源电流参考值的幅值,再结合源电压的角频率计算参考电流,最后采取李亚普诺夫方法设计APF的开关函数,通过确保能量函数的导数始终为负来保证系统的全局稳定。通过Matlab/Simulink中的自适应神经模糊系统对TS模糊控制器的参数进行优化,并且进行对比实验。结果表明,在负载时变和系统参数变化的情况下,该控制方法可以保证系统的稳定鲁棒性和控制精度。

In allusion to the difficulty of achieving accurate mathematical model of active power filter（APF） and the problem of control system stability,the Takagi-Sugeno（TS） fuzzy control and the control approach based on Lyapunov stability theory are led into DC voltage control and current control of APF to ensure the control accuracy and stability. Firstly,the TS fuzzy control is applied to voltage error and error rate at DC side to attain the source current amplitude of reference value;then based on the angular frequency of source voltage the reference current is calculated;finally the Lyapunov method is adopted to design the switching function of APF and the global stability of control system is ensured by insuring the derivative of energy-like Lyapunov function always negative. By means of adaptive fuzzy neural system in Matlab/Simulink the parameters of TS fuzzy controller are optimized and contrast experiments are performed.Results of contrast experiments show that under the time-varying load and variation of power system parameters both robustness and control accuracy of the control system can be ensured by the proposed control method.