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Comparative study of constraint optimizations for automatic voltage regulator

机译:自动电压调节器约束优化的比较研究

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A notable literature is available on optimal design of PID parameters using various evolutionary algorithms. The proper selection of an optimization algorithm is significantly important in finding the robust solution for a given optimization problem. Two most powerful optimization techniques are cuckoo optimization algorithm (COA) and particle swarm optimization (PSO). In this paper, a tight constraint is developed to ensure the less variation in the control input signal and at the same time the overall dynamic performance is not compromised for automatic voltage regulator (AVR) system. Then, using two metaheuristic search algorithms the optimal tune techniques are implemented by imposing the performance index. The presented performance index performs well in the presence of the uncertainties in system parameters. A result is discussed in the simulation study.
机译:有关使用各种进化算法对PID参数进行最佳设计的著名文献。正确选择优化算法对于找到给定优化问题的鲁棒解决方案非常重要。两种最强大的优化技术是布谷鸟优化算法(COA)和粒子群优化(PSO)。本文提出了一个严格的约束条件,以确保控制输入信号的变化较小,同时对于自动电压调节器(AVR)系统,其整体动态性能不会受到影响。然后,使用两种元启发式搜索算法,通过施加性能指标来实现最佳调谐技术。在系统参数存在不确定性的情况下,给出的性能指标表现良好。仿真研究中讨论了结果。

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