【作者】 余向阳；

【导师】 南海鹏；

【作者基本信息】 西安理工大学 ， 水利水电工程， 2003， 硕士

【摘要】 本文针对水轮机调节系统的控制问题，以指令扰动和甩负荷系统响应特性为优化目标，提出采用遗传算法优化水轮机模糊PID控制，实现调节参数最优整定以及基于优化模糊规则的适应式参数自调整PID控制策略。 提出一种可变交叉概率和变异概率的改进遗传算法进行调节参数优化的方法，仿真结果表明，该方法有效地消除了对参数初值的依赖性，使得寻优效率大大提高，同时具有较强的鲁棒性，是一种较好的PID参数寻优方法。 结合智能控制理论和软计算技术，提出了基于模糊规则的适应式参数自调整PID控制策略。它将模糊推理与传统PID控制相结合，使调速器进一步适应调节系统工况的变化。对于模糊推理中的模糊规则和隶属函数，利用遗传算法进行寻优，以确保得到适合水轮机调节系统的模糊规则。仿真结果表明基于模糊规则的适应式参数自调整PID控制策略是行之有效的。更多还原

【Abstract】 In this paper, in order to solve the self-adaptive control of hydraulic turbine governor, An optimization method of fuzzy PID control strategy based on dynamic performance using genetic algorithms is proposed. It realizes PID control parameters self-adjusting accordingA new improving genetic algorithm with the alterable intercross probability and mutation probability to optimize the parameters of hydro turbine governor is presented. The simulation result suggests that it doesn’t depend on the initial parameter value of the system. The searching efficiency can be ameliorated. At the same time, it has strong robustness and is an excellent PID optimization method.Referred the intelligent control theory, the self-adjusting parameter PID control strategy based on the fuzzy logic rules is proposed. Combining the fuzzy logic and traditional PID control, it makes governor more adaptive to the real conditions. Since the fuzzy reasoning rules are difficult to make, we apply the improving genetic algorithms to optimize the fuzzy reasoning rules and thus can obtain the excellent fuzzy reasoning rule sets. The simulation result shows that the self-adjusting PID control strategy based on the fuzzy reasoning rules is more available.更多还原