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。
And the use of orthogonal test conducted on the hydro-turbine governing system parameters PID conditioning system optimization, have been better adjustment parameters.
并采用正交试验法对水轮机调节系统进行PID调节系统参数的优化，得到了效果较好的调节参数。
Particle swarm optimization algorithm is also adopted to optimize parameters of PID controller.
PID控制器参数由粒子群算法进行优化。
The parameters of the PID controllers, however, are very much dependent on the accuracy of the models. This paper studies the control algorithms for aeroengines based on intelligent optimization.
本文重点研究如何利用先进的智能优化算法改进传统的发动机控制系统，并进一步对前沿的智能控制算法及其研究方向进行探索性研究。
The parameters of the PID controllers, however, are very much dependent on the accuracy of the models. This paper studies the control algorithms for aeroengines based on intelligent optimization.
本文重点研究如何利用先进的智能优化算法改进传统的发动机控制系统，并进一步对前沿的智能控制算法及其研究方向进行探索性研究。
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