基于分布种群遗传算法的控制器优化设计研究
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摘要
遗传算法作为一种新型优化算法,由于具有简单、易操作、并行信息处理等特点,已经在许多领域的优化问题求解方面取得了成功的应用。但是遗传算法在理论上还不够完善,例如存在容易产生早熟现象以及局部寻优能力较差等问题,影响了其进一步的应用。本文针对常规遗传算法的不足,受生物种群分布的启发,提出了一种基于分布种群的遗传算法,将这种算法运用到单变量和多变量控制器参数优化整定,并进行仿真实验研究。
本文主要内容包括以下几个方面:
1.综述了遗传算法的产生、发展和现状以及在控制器参数优化整定方面的研究
概况;介绍了遗传算法的基本原理和方法,给出了遗传算法存在的问题以及对此进行的改进工作。
2.针对常规遗传算法的不足,受生物种群分布的启发,提出了一种基于分布种群的遗传算法,将该算法运用于PID控制器参数优化整定,进行了仿真试验
研究,结果表明了该算法的有效性。
3.针对单变量智能控制器,使用基于分布种群的遗传算法对神经元PID控制器和模糊神经元非模型控制器进行了参数优化整定,对具有时变、非线性和不确定的水轮发电机组和车削过程进行的仿真控制实验表明优化整定后的控制器在控制性能上有了明显的提高。
4.使用基于分布种群的遗传算法对多变量神经PID控制器的参数进行了优化整定和火电单元机组、多侧线精馏塔的仿真控制试验研究,结果表明了所设计的控制器具有优良的控制品质和较强的鲁棒性。
As a new optimization method, GA was widely used in the optimizations of many fields owing to the features of simplicity, easily handing and parallel processing. However GA theory is not prefect,such as there exist the problems of easily creating earliness and bad ability in local optima,etc. Enlightened by distribution of creature living in natural ecology environment, the Distribution Population based Genetic Algorithm (DPGA) is proposed in this paper. DPGA is applied to optimize the controller parameters for single variable systems and multi-variable systems. The simulation tests are made and the results demonstrate the efficiency of the proposed method. The main content of this thesis includes the following:1. A survey of the origin and the development status of genetic algorithm is summarized and the status of the parameter optimization of controllers is introduced. Also the principles of GA are introduced and the problems for further study on GA are given.2. Enlightened by distribution of creature living in natural ecology environment, the Distribution Population based Genetic Algorithm is proposed. Then DPGA is applied to obtain the optimal parameters of PID controllers.3. DPGA is used to get the optimal parameters of the neuron PID controller and the neuro-fuzzy controller. Simulation experiments results of controlling the hydraulic turbine generator and the cutting process show that the better performances of the controllers are reached.4. The multivariable neuron-PID controller based on DPGA is designed for the plants of the unit power plant and the distillation towers with multiple side-streams. The simulation tests of controlling a unit power plant and a distillation process are made and the results demonstrate the efficiency of the optimal multivariable controller.
本文主要内容包括以下几个方面:
1.综述了遗传算法的产生、发展和现状以及在控制器参数优化整定方面的研究
概况;介绍了遗传算法的基本原理和方法,给出了遗传算法存在的问题以及对此进行的改进工作。
2.针对常规遗传算法的不足,受生物种群分布的启发,提出了一种基于分布种群的遗传算法,将该算法运用于PID控制器参数优化整定,进行了仿真试验
研究,结果表明了该算法的有效性。
3.针对单变量智能控制器,使用基于分布种群的遗传算法对神经元PID控制器和模糊神经元非模型控制器进行了参数优化整定,对具有时变、非线性和不确定的水轮发电机组和车削过程进行的仿真控制实验表明优化整定后的控制器在控制性能上有了明显的提高。
4.使用基于分布种群的遗传算法对多变量神经PID控制器的参数进行了优化整定和火电单元机组、多侧线精馏塔的仿真控制试验研究,结果表明了所设计的控制器具有优良的控制品质和较强的鲁棒性。
As a new optimization method, GA was widely used in the optimizations of many fields owing to the features of simplicity, easily handing and parallel processing. However GA theory is not prefect,such as there exist the problems of easily creating earliness and bad ability in local optima,etc. Enlightened by distribution of creature living in natural ecology environment, the Distribution Population based Genetic Algorithm (DPGA) is proposed in this paper. DPGA is applied to optimize the controller parameters for single variable systems and multi-variable systems. The simulation tests are made and the results demonstrate the efficiency of the proposed method. The main content of this thesis includes the following:1. A survey of the origin and the development status of genetic algorithm is summarized and the status of the parameter optimization of controllers is introduced. Also the principles of GA are introduced and the problems for further study on GA are given.2. Enlightened by distribution of creature living in natural ecology environment, the Distribution Population based Genetic Algorithm is proposed. Then DPGA is applied to obtain the optimal parameters of PID controllers.3. DPGA is used to get the optimal parameters of the neuron PID controller and the neuro-fuzzy controller. Simulation experiments results of controlling the hydraulic turbine generator and the cutting process show that the better performances of the controllers are reached.4. The multivariable neuron-PID controller based on DPGA is designed for the plants of the unit power plant and the distillation towers with multiple side-streams. The simulation tests of controlling a unit power plant and a distillation process are made and the results demonstrate the efficiency of the optimal multivariable controller.
引文
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[22] Zhang Feizhou, Yang Dongkai, Chen Xiuwan, Intelligent Scheduling of Public Traffic Vehicles based on Hybrid Genetic Algorithm, Intelligent Transportation Systems, 2003 Proceedings, 2:1674-1678, 2003
[23] Il-Seok Oh, Jin-Seon Lee, Byung-Ro Moon, Hybrid Genetic Algorithms for Feature Selection, Pattern Analysis and Machine Intelligence, 26(11):1424-1437, 2004
[24] 沈艳军,汪秉文,基于实数编码的克隆选择算法及其应用,华中科技大学学报:自然科学版,32(2):41-42,2004
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[32] 张晓绩,戴冠中,徐乃平,遗传算法在抽取和过滤模糊控制规则中的应用研究,控制理论和应用,15(2):379-384,1998
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[35] 云庆夏,遗传算法和遗传规划;一种搜索寻优技术,冶金工业出版社,北京,1997
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[37] Ludvig, J., J.Hesser, and R. Manner, Tackling the Representation Problem by Stochastic Averaging, Proceedings of the 7th International Conference on Genetic Algorithms, Morgan Kaufman Publishers, San Francisco, 196-203, 1997
[38] Eshelman, L and J. Schaffer, Real-coded Genetic Algorithms and Interval schemata, Foundations of Genetic Algorithms, 2:187-202, 1993
[39] McCormick, W.T., P.J. Schweitzer, and T. W. White, Problem Decomposition and Data Reorganization by a Cluster Technique, Operations Research, 20(5):993-1009, 1972
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