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传统PID控制器通常难以满足多变量、非线性、强耦合的步进电机动态响应和精
确调速要求,结合传统PID控制和模糊控制及遗传算法(GA)整定PID参数的优点,设计基于
模糊遗传算法的实时自适应步进电动机PID控制器,充分发挥传统和智能控制策略各自的优
势。仿真结果表明,该实时自适应步进电动机PID控制器,具有很好的自适应能力和抗负载扰
动能力。在稳定性、动态速度响应诸方面均优于传统的PID控制器和模糊控制器,系统达到了
较高调速性能和控制精度。
-Traditional PI
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目前，有许多方法用来
研究多电机同步控制策略，本文采用的是偏差藕合控制方法，利用模糊PD作为速度
同步补偿器的控制算法，使用遗传算法来整定Por的参数范围，解决了多电机同步控
制系统中多电机速度的同步控制问题。-At present, there are many methods used to
Study of the motor synchronous control strategy used in this paper is the deviation of coupli
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识获取的模糊控制系统的基础上改进的遗传算法和神经网络
-Knowledge Acquisition of Fuzzy Control System Based on Improved Genetic
Algorithm and Neural Networks
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A GENETIC-BASED FUZZY LOGIC POWER SYSTEM STABILIZER FOR
MULTIMACHINE POWER SYSTEMS
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Design of Genetic Algorithm Based Fuzzy
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Optimal power flow (OPF) is one of the nonlinear problems of power system. The various
algorithms for solving optimal power flow problem are found in the literature. The genetic algorithm
(GA) based solution techniques are found to be most suitab
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In this paper,we address the effect of illumination on the face detection and the face recognition problem by introducing a novel illumination invariant method, called OptiFuzz. It is an optimized fuzzy-based illumination invariant method to solve th
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A Genetic Fuzzy System (GFS) is basically a fuzzy system augmented by a learning process based on a Q3
genetic algorithm (GA). Fuzzy systems have demonstrated their ability to solve different kinds of problems in various application domains. Curren
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粒子群优化（PSO）是一种进化计算技术（进化计算）。
捕食鸟行为的研究。粒子群算法（PSO）的基本思想是通过群体中个体之间的协作和信息共享找到最优解。
粒子群优化算法的优点是它简单且易于实现，没有多个参数。目前，它已广泛应用于函数优化、神经网络训练、模糊系统控制等遗传算法中。(The particle swarm optimization (PSO:Particle swarm optimization) is an evolutionary computing technology (Ev
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