提出一種將單純形法SM與粒子群算法PSO結合的混合粒子群算法HPSO。通過對3種常用測試函數進行優化和比較，結果表明HPSO比PSO和SM都更容易找到全局最優解。然后用HPSO優化算法對某渦扇發動機PID控制中的參數進行優化并將結果與混合遺傳算法HGA的結果進行比較，結果表明HPSO在找尋最優解效率上好于HGA。且算法實現簡單,具有很高的可靠性,是一種PID控制參數尋優的有效方法。
關鍵詞: 粒子群優化算法; 單純形算法; 航空發動機; PID控制; 遺傳算法

Optimization Methodology of PID Parameters for Aeroengines Based on Hybrid PSO CAO Zhi-song, PIAO Ying (School of Aerospace, Tsinghua University, Beijing 100084, China) Abstract: A hybrid particle swarm optimization algorithm (HPSO) was proposed based on PSO and simplex method (SM). HPSO, PSO and SM are used to resolve three widely used test functions’ optimization problems. Results show that HPSO has greater efficiency and better performance than PSO and SM. HPSO is used to optimize the aeroengine PID controller parameters, and the result indicates that HPSO can obtain the optimum solutions more easily than HGA. Although very easy to implement, this HPSO is an efficient way to optimize the PID controller parameters.
Key words: particle swarm optimization(PSO); simplex algorithm(SM); aeroengine; PID control;