基于模糊自适应和模拟退火优化的混合H2/H∞鲁棒PID电力系统稳定器设计

A. Ghany
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引用次数: 7

摘要

本文将混合H2/Hinfin控制理论和模拟退火(SA)技术结合自适应神经模糊推理系统(ANFIS)设计了两个自适应鲁棒输出反馈控制器。第一个控制器是混合H2/Hinfin,使用线性矩阵不等式(LMI)技术求解。第二种是鲁棒PID,它在工业中非常实用,通过SA对混合H2/Hinfin规范进行优化,找到了最优参数。对H2/Hinfin混合范数的计算采用消极操作。前者的特点是与可能更高阶的工厂大小相似,因此在大型系统中实施起来很困难。从实现的角度来看,后者更健壮,更有吸引力,因为它的大小更小。设计了两个ANFISs。第一个ANFIS系统(ANFISS),用于预测系统参数。第二个ANFIS控制(ANFISC)用于附加相应的PID增益的优化控制设置。运行条件代表每个ANFIS的输入,由发电机的有功功率输出和终端电压定义。这两种控制器都用作单机无限母线系统的电力系统稳定器。所提出的控制器在较宽的工作条件和参数变化范围内具有鲁棒性。
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Design of a mixed H2/H∞ robust PID power system stabilizer with fuzzy adaptation and Simulated Annealing optimization
In this paper, a mixed H2/Hinfin control theory and simulated annealing (SA) techniques in conjunction with adaptive neuro-fuzzy inference system (ANFIS) are combined to design two adaptively robust output feedback controllers. The first controller is a mixed H2/Hinfin that is solved using linear matrix inequalities (LMI) technique. The second one, robust PID, which is ideally practical for industry, whose optimum parameters are found using the optimization of mixed H2/Hinfin norms via SA. Canceling pole operation is used to perform the calculations of mixed H2/Hinfin norms. The former is characterized by a similar size as the plant that may be of higher order and thus creates difficulty in implementation in large systems. The latter is shown to be robust and more appealing from an implementation point of view since its size is lower. Two ANFISs are designed. The first ANFIS system (ANFISS), is used to predict the system parameters. The second ANFIS control (ANFISC) , is used to append the corresponding optimized control setting of the PID gains. The operating conditions represent the inputs of each ANFIS defined by the generator active power output, and terminal voltage. Both controllers are used as a power system stabilizer for a single-machine infinite bus system. The proposed controllers show robustness over a wide range of operating conditions and parameters change.
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