初步研究Z源逆变器用于光伏并网逆变系统中的强耦合和非线性问题,探索光伏阵列的最大功率跟踪(Maximum Power Point Tracking-MPPT)和直流侧稳压统一控制的方法,采用非对称输入输出多变量PID神经网络控制,抑制直流侧电压扰动,通过三相...初步研究Z源逆变器用于光伏并网逆变系统中的强耦合和非线性问题,探索光伏阵列的最大功率跟踪(Maximum Power Point Tracking-MPPT)和直流侧稳压统一控制的方法,采用非对称输入输出多变量PID神经网络控制,抑制直流侧电压扰动,通过三相电流跟踪解耦控制实现MPPT和单位功率因数并网。仿真实验结果表明,该控制策略能有效抑制由光伏阵列输出变化、电网波动及其他干扰对直流侧电压的扰动。展开更多
Based on the ant colony system （ACS） algorithm and fuzzy logic control, a new design method for optimal fuzzy PID controller was proposed. In this method, the ACS algorithm was used to optimize the input/output scal...Based on the ant colony system （ACS） algorithm and fuzzy logic control, a new design method for optimal fuzzy PID controller was proposed. In this method, the ACS algorithm was used to optimize the input/output scaling factors of fuzzy PID controller to generate the optimal fuzzy control rules and optimal real-time control action on a given controlled object. The designed controller, called the Fuzzy-ACS PID controller, was used to control the CIP-Ⅰ intelligent leg. The simulation experiments demonstrate that this controller has good control performance. Compared with other three optimal PID controllers designed respectively by using the differential evolution algorithm, the real-coded genetic algorithm, and the simulated annealing, it was verified that the Fuzzy-ACS PID controller has better control performance. Furthermore, the simulation results also verify that the proposed ACS algorithm has quick convergence speed, small solution variation, good dynamic convergence behavior, and high computation efficiency in searching for the optimal input/output scaling factors.展开更多
文摘初步研究Z源逆变器用于光伏并网逆变系统中的强耦合和非线性问题,探索光伏阵列的最大功率跟踪(Maximum Power Point Tracking-MPPT)和直流侧稳压统一控制的方法,采用非对称输入输出多变量PID神经网络控制,抑制直流侧电压扰动,通过三相电流跟踪解耦控制实现MPPT和单位功率因数并网。仿真实验结果表明,该控制策略能有效抑制由光伏阵列输出变化、电网波动及其他干扰对直流侧电压的扰动。
基金Project(50275150) supported by the National Natural Science Foundation of ChinaProject(20040533035) supported by the National Research Foundation for the Doctoral Program of Higher Education of ChinaProject(05JJ40128) supported by the Natural Science Foundation of Hunan Province, China
文摘Based on the ant colony system （ACS） algorithm and fuzzy logic control, a new design method for optimal fuzzy PID controller was proposed. In this method, the ACS algorithm was used to optimize the input/output scaling factors of fuzzy PID controller to generate the optimal fuzzy control rules and optimal real-time control action on a given controlled object. The designed controller, called the Fuzzy-ACS PID controller, was used to control the CIP-Ⅰ intelligent leg. The simulation experiments demonstrate that this controller has good control performance. Compared with other three optimal PID controllers designed respectively by using the differential evolution algorithm, the real-coded genetic algorithm, and the simulated annealing, it was verified that the Fuzzy-ACS PID controller has better control performance. Furthermore, the simulation results also verify that the proposed ACS algorithm has quick convergence speed, small solution variation, good dynamic convergence behavior, and high computation efficiency in searching for the optimal input/output scaling factors.
