基於改良式灰狼演算法之最佳PID水溫控制器設計

PID-BASED WATER TEMPERATURE CONTROLLER DESIGN USING A MODIFIED GREY WOLF OPTIMIZER

本文擬提出改良式灰狼演算法（Modified Grey Wolf Optimizer; MGWO）應用於求解PID控制器參數最佳化問題，利用灰狼演算法（Grey Wolf Optimizer; GWO）中係數向量設計參數之改良，本文所提方法可同時強化其全域探勘及區域開發之搜尋能力，以改善GWO容易陷入局部最佳解的問題。為改善傳統電加熱器on-off控制系統溫度控制性能差、長時間運轉耗能高之問題，本研究擬建置一套以MGWO最佳化技術為基礎之PID溫度控制系統，並且將其應用於電熱水壺之水溫控制。模擬結果證明在PID控制器增益參數之設計中，相較於傳統GWO，所提的MGWO改良方法能有較佳的控制性能與系統響應。實驗結果顯示，比起傳統on-off控制器，本文所提之MGWO結合PID控制器於電熱水壺應用中可利用較低耗能獲得更佳的溫度控制性能。

In this paper, a modified algorithm based on grey wolf optimizer (GWO) method is developed to design the parameters of proportional-integral-derivative (PID) controller. Using a novel coefficient vectors, the modified grey wolf optimization (MGWO) method has better global and local search capabilities as well as avoids the problem of premature convergence. To improve the performance of on-off temperature controller, a PID-based temperature controller using the MGWO technique is developed to control water temperature of the electric kettle. Numerical experiments are included to demonstrate the proposed MGWO approach can obtain a higher quality solution than the GWO technique for the PID controller optimization design. The proposed PID-based water temperature controller also gives more satisfactory performance than that of the on-off temperature controller for electric kettle.