基于粒子群优化自适应反推光伏并网逆变器控制研究

Research on a Particle Swarm Optimization Adaptive Backstepping Control Method of Grid-connected Inverters

常规反推控制存在控制子系统转换复杂和控制噪声的问题,而且在系统存在外部扰动和参数摄动的情形下,需要详细的控制系统信息和增加额外的补偿控制。针对这个问题,提出一种基于粒子群优化自适应反推控制的光伏并网逆变器控制方法。首先基于瞬时功率和空间矢量理论,建立包含电网和并网逆变器参数摄动和外部扰动的动态数学模型。然后,设计粒子群优化算法直接逼近反推控制的控制量,省掉子系统转换和非线性补偿环节,简化了控制系统结构。最后,根据李雅普诺夫(Liyapunov)稳定性分析,求解自适应律,并在线调整粒子群优化算法进化参数。实验结果证明该方法的有效性和鲁棒性。

In order to cope with the problem of the complicated control transformation and the chattering control effort in backstepping control design, and to directly ensure the stability of the controlled system without the requirement of strict constraints, detailed system information and auxiliary compensated controller despite the existence of uncertainties, an on-line particle swarm optimization adaptive backstepping control method is designed in this paper. The dynamic model of grid-connected inverters including grids and inverters based on the concepts of the instantaneous power theory and the space vector is first constructed. In the proposed particle swarm optimization backstepping control（PSOBSC） scheme, a particle swarm optimization（PSO） control is utilized to identify the backstepping control efforts directly without subsystem transform and nonlinear compensated. And then adaptation laws derived from Lyapunov stability analyses are manipulated to adjust appropriate evolutionary coefficients. The effectiveness of the proposed control strategy for grid-connected is verified by experimental results.