优化有源电力滤波器(active power filter,APF)直流侧电压自抗扰控制(active disturbance rejection control,ADRC)参数的粒子群优化算法(particle swarm optimization algorithm,PSOA)优化参数的精度低、粒子易陷入局部最优.针对其缺点,提出了一种优化APF直流侧电压ADRC参数的自适应粒子群优化算法(adaptive PSOA,APSOA).在PSOA的基础上,APSOA自适应调节惯性权重和学习因子,并引入正弦分段混沌映射和混合变异因子,以避免粒子陷入局部最优,加快算法优化速度,提高算法优化参数的精度.仿真结果证实,相对于使用PSOA优化参数的APF直流侧电压ADRC,使用APSOA优化参数的APF直流侧电压ADRC的直流侧电压的响应速度更快,稳态误差更小,电网电流的总谐波畸变率更小.因此,相对于优化APF直流侧电压ADRC参数的PSOA,提出的优化APF直流侧电压ADRC参数的APSOA优化参数的精度更高.
Adaptive Particle Swarm Optimization Algorithm for Optimizing Parameters of Active Disturbance Rejection Control of DC-link Voltage of APF
The particle swarm optimization algorithm(PSOA)for optimizing the parameters of active disturbance rejec-tion control(ADRC)of the DC-link voltage of an active power filter(APF)has low accuracy of its optimized parame-ters,and its particles easily fall into local optimum.Against its shortcomings,an adaptive PSOA(APSOA)for optimiz-ing the parameters of ADRC of the DC-link voltage of an APF is proposed in this paper.On the basis of the PSOA,the proposed APSOA adaptively adjusts the inertia weight and learning factor and introduces the sine piece-wise chaotic mapping and mixed variation factor to avoid its particles falling into local optimum,to accelerate its op-timization speed,and to improve the accuracy of its optimized parameters.Finally,simulation results demonstrate that the APF DC-link voltage ADRC using parameters optimized by the APSOA has a faster response speed and a small-er steady-state error of the DC-link voltage and lower THD(total harmonic distortion)of the grid current than by the PSOA does.Therefore,the APSOA has higher accuracy of optimizing the parameters of the APF DC-link voltage ADRC than the PSOA does.
active power filter(APF)DC-link voltage controlparticle swarm optimization algorithm(PSOA)active dis-turbance rejection control(ADRC)
万方数据
维普
