毕业论文--基于遗传算法的PID参数优化设计.doc

摘 要 PID调节器是最早发展起来的控制策略之一，遗传算法是一种借鉴生物界自然选择和自然遗传学机理上的迭代自适应概率性搜索算法。本文提出了一种基于遗传算法的PID控制器参数优化设计。遗传算法模仿生物进化的步骤，在优化过程中引入了选择，交叉，变异等算子，选择是从父代种群中将适应度较高的个体选择出来，以优化种群；交叉是从种群中随机地抽取一对个体，并随机地选择多位进行交叉，生成新样本，达到增大搜索空间的目的；变异是为了防止选择和交叉丢失重要的遗传信息，它对个体按位进行操作，以提高GA的搜索效率和全局搜索能力。通过适应度函数来确定寻优方向，与其他一些常规整定方法相比，遗传算法比较简便，整定精度较高。本文用遗传算法对柴油机调速系统的PID参数进行了优化，对该系统进行了仿真，实验结果表明该种算法的有效性，也表明遗传算法是一种简单高效的寻优算法，与传统的寻优方法相比明显地改善了控制系统的动态性能。 关键词：遗传算法；PID控制器；参数优化Based on genetic algorithm optimization of PID parameters Abstract PID regulator is one of the first developed one of the control strategy, genetic algorithm is a kind of natural selection from biological genetics and natural mechanism of the iterative adaptive probabilistic search algorithm. In this paper, a genetic algorithm based on the Optimal Design of PID controller parameters. Genetic algorithms to imitate the steps of biological evolution, in the optimization process of the introduction of selection, crossover and mutation operators, etc., choose from the parent population will adapt to a higher degree of individual choice in order to optimize the population; cross randomly from the population to collect a pair of individuals, and a number of randomly selected cross, generate new samples, to achieve the purpose of increasing search space; variation is to prevent the loss of choice and cross-important genetic information, carried out by its individual operations, in order to enhance GAs search efficiency and global search ability. Through the fitness function to determine the optimal direction, and setting a number of other conventional methods, genetic algorithm is simple, accurate tuning. In this paper, genetic algorithm of the PID speed control system of diesel engine parameters are optimized, the system simulation, experimental results show that the algorithm also shows that the genetic algorithm is a simple and efficient optimization algorithm, with the traditional optimization methods significantly improved the control system dynamic perform