Genetic Algorithm and Particle Swarm Optimization tuned Fractional Order Pitch Angle Control

S. Karad, Ritula Thakur
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引用次数: 1

Abstract

Modelling and control of complex non-linear systems is always important area of investigation in different fields of engineering applications. Since last decade fractional order control emerge as an efficient strategy for modelling and control of complex non-linear systems and shown the efficiency. Also, recently intelligent control strategies based on various AI techniques shown their efficiency in various fields such as process control, power system, renewable energy, etc. This paper applies Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) tuned intelligent fractional order pitch regulator for doubly fed induction generator (DFIG) based wind turbine (WT) system. Proposed scheme is modelled and simulated using Matlab/Simulink to analyze its time domain performance for a step input as well as tracking response with ITAE and IAE index.
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遗传算法与粒子群优化调谐分数阶俯仰角控制
复杂非线性系统的建模与控制一直是工程应用领域的重要研究领域。近十年来,分数阶控制作为一种有效的复杂非线性系统建模和控制策略逐渐出现,并显示出其有效性。近年来,基于各种人工智能技术的智能控制策略在过程控制、电力系统、可再生能源等各个领域都显示出其效率。将遗传算法(GA)和粒子群优化(PSO)相结合的智能分数阶节距调节器应用于双馈感应发电机风力发电系统。利用Matlab/Simulink对该方案进行了建模和仿真,分析了该方案在阶跃输入下的时域性能以及ITAE和IAE指标下的跟踪响应。
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