自然启发的元启发式优化用于复杂系统的控制调整.
Jesús Garicano-Mena1,2, Matilde Santos3
1ETSI Aeronáutica y del Espacio-Universidad Politécnica de Madrid, 28040 Madrid, Spain.
Biomimetics (Basel, Switzerland)
|January 24, 2025
概括
这项研究提出了元启发式优化算法,Antlion Optimizer (ALO) 和Whale Optimization Algorithm (WOA),用于调整动态系统中的控制器. 这两种算法在优化电机和风力轮机系统的PID控制器方面表现相似.
科学领域:
- 控制系统工程 控制系统工程
- 计算智能是一种计算智能.
- 优化技术 优化技术
背景情况:
- 针对复杂动态系统的调控制器,包括机电和风力轮机系统,存在重大挑战.
- 超启发式优化算法为解决这些复杂的调整问题提供了有希望的方法.
研究的目的:
- 提出和评估一种方法来实现最佳的控制器调整,使用生物启发的元启发式技术.
- 为了比较Antlion优化器 (ALO) 和鱼优化算法 (WOA) 的性能,用于调整比例-整数-导数 (PID) 控制器.
主要方法:
- 应用Antlion优化器 (ALO) 和鱼优化算法 (WOA) 在两个不同的动态系统上:一个Hoop & Ball电机系统和一个风力轮-发电机-整流器.
- 基于诸如代理数 (nS) 和最大代 (nMaxIter) 等参数的控制器调整性能评估.
- 评估与ALO和WOA实施相关的可重复性和计算力度.
主要成果:
- 在对线化电机系统和复杂的非线性风力轮机系统的PID控制器调方面,ALO和WOA都取得了可比的结果.
- 对两种算法的性能进行了分析,涉及到代理和代的数量,同时也考虑了可重复性.
- 评估了实施ALO和WOA的计算工作.
结论:
- 安特利安优化器 (ALO) 和鱼优化算法 (WOA) 是在动态系统中进行最佳控制器调整的有效和可比方法.
- 这些元启发式技术可以互补,允许在控制器设计中利用单个算法的优势.
- 这些发现支持使用ALO和WOA来优化各种工程应用中的传统PID控制器.
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