This dissertation presents the studies of genetic algorithms (GA) based model structure and parameters conjunct identification, PID optimization, and the engineering application method.
本论文是基于遗传算法(GA)的模型结构和参数共同辨识、PID参数的优化整定和工程应用方法的研究。
In light of traditional PID controller parameters optimization with manual cut-and-try method, a novel kind of PID parameters optimization strategy based on ACA (Ant Colony Algorithm) was proposed.
针对传统的PID控制器参数多采用试验加试凑的方式由人工进行优化，提出了一种新型的基于蚁群算法的PID参数优化策略。
To gain optimization parameters of hydro turbine PID governor, this paper interprets the approach of optimization designing that uses the Particle Swarm Optimization (PSO) algorithm.
为了保证获得最优水轮机PID调节器参数，本文研究了利用微粒群优化（PSO）算法进行参数优化设计的新方法。
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