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Current Search: Performance Evaluation and Application to DC Motor Speed Control System Design

机译：当前搜索：性能评估及其在直流电动机调速系统设计中的应用

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摘要

This paper proposes the current search (CS) metaheuristics conceptualized from the electric current flowing through electric networks for optimization problems with continuous design variables. The CS algorithm possesses two power-ful strategies, exploration and exploitation, for searching the global optimum. Based on the stochastic process, the de-rivatives of the objective function is unnecessary for the proposed CS. To evaluate its performance, the CS is tested against several unconstrained optimization problems. The results obtained are compared to those obtained by the popu-lar search techniques, i.e., the genetic algorithm (GA), the particle swarm optimization (PSO), and the adaptive tabu search (ATS). As results, the CS outperforms other algorithms and provides superior results. The CS is also applied to a constrained design of the optimum PID controller for the dc motor speed control system. From experimental results, the CS has been successfully applied to the speed control of the dc motor.
机译：本文提出了从流经电网的电流概念化的电流搜索（CS）元启发式方法，以解决具有连续设计变量的优化问题。 CS算法拥有两种强大的策略，即探索和开发，用于搜索全局最优值。基于随机过程，目标函数的导数对于所提出的CS是不必要的。为了评估其性能，对CS进行了无限制优化问题的测试。将获得的结果与通过大众搜索技术（即遗传算法（GA），粒子群优化（PSO）和自适应禁忌搜索（ATS））获得的结果进行比较。结果，CS胜过其他算法并提供了出色的结果。 CS还应用于直流电动机速度控制系统的最佳PID控制器的约束设计。从实验结果来看，CS已成功应用于直流电动机的速度控制。

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