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Fuzzy Controller Design Using Evolutionary Techniques for Twin Rotor MIMO System: A Comparative Study

机译:基于进化技术的双转子MIMO系统模糊控制器设计的比较研究

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摘要

This paper presents a comparative study of fuzzy controller design for the twin rotor multi-input multioutput (MIMO) system (TRMS) considering most promising evolutionary techniques. These are gravitational search algorithm (GSA), particle swarm optimization (PSO), artificial bee colony (ABC), and differential evolution (DE). In this study, the gains of four fuzzy proportional derivative (PD) controllers for TRMS have been optimized using the considered techniques. The optimization techniques are developed to identify the optimal control parameters for system stability enhancement, to cancel high nonlinearities in the model, to reduce the coupling effect, and to drive TRMS pitch and yaw angles into the desired tracking trajectory efficiently and accurately. The most effective technique in terms of system response due to different disturbances has been investigated. In this work, it is observed that GSA is the most effective technique in terms of solution quality and convergence speed.
机译:本文针对双转子多输入多输出(MIMO)系统(TRMS)的模糊控制器设计进行了比较研究,考虑了最有前途的进化技术。这些是重力搜索算法(GSA),粒子群优化(PSO),人工蜂群(ABC)和差异进化(DE)。在这项研究中,已使用考虑的技术对四个TRMS的模糊比例微分(PD)控制器的增益进行了优化。开发了优化技术以识别用于增强系统稳定性的最佳控制参数,以消除模型中的高非线性度,以减小耦合效应,并有效且准确地将TRMS俯仰角和偏航角驱动到所需的跟踪轨迹中。研究了由于不同干扰而引起的系统响应方面最有效的技术。在这项工作中,可以观察到,就解决方案质量和收敛速度而言,GSA是最有效的技术。

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