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Tuning of PID controllers with CMAC-based genetic algorithm

机译:基于CMAC遗传算法的PID控制器整定

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Based on cerebellar model articulation controller (CMAC), this paper attempts to propose a new chromosome representation scheme for representing real number parameters in genetic algorithms (GAs), which is termed CMAC-based GAs. The central idea of CMAC-based GAs is that each memory unit in a CMAC network is regarded as a real-valued gene in GAs. By this way, a chromosome is represented as those memory units addressed by a specific state and each gene involves partial information about a potential solution, not a potential solution as the conventional GAs. In addition, the corresponding crossover and mutation operators are also derived for the proposed GAs. The proposed CMAC-based GAs is applied to optimize the parameters of the proportional-integral-derivative controller. Simulation results are compared with several previous findings to demonstrate the search performance of the proposed method.
机译:基于小脑模型关节控制器(CMAC),本文试图提出一种新的代表遗传算法(GA)中实数参数的染色体表示方案,称为基于CMAC的遗传算法。基于CMAC的GA的中心思想是CMAC网络中的每个存储单元都被视为GA中的实值基因。通过这种方式,染色体被表示为通过特定状态寻址的那些存储单元,并且每个基因都包含有关潜在解决方案的部分信息,而不是常规GA的潜在解决方案。此外,还为拟议的遗传算法推导了相应的交叉和变异算子。提出的基于CMAC的遗传算法被应用于优化比例积分微分控制器的参数。仿真结果与以前的发现进行了比较,以证明该方法的搜索性能。

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