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首页> 外文期刊>Aerospace science and technology >Robust fuzzy linear quadratic regulator control optimized by multi-objective high exploration particle swarm optimization for a 4 degree-of-freedom quadrotor
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Robust fuzzy linear quadratic regulator control optimized by multi-objective high exploration particle swarm optimization for a 4 degree-of-freedom quadrotor

机译：四自由度四旋翼多目标高探索粒子群算法优化的鲁棒模糊线性二次调节器控制

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摘要

In this article, a robust fuzzy controller based on the Linear Quadratic Regulator (LQR) method is presented and optimized by Multi-Objective High Exploration Particle Swarm Optimization (MOHEPSO) for a nonlinear 4 Degree-Of-Freedom (DOF) quadrotor. The LQR approach is applied after linearization via Jacobean matrices. The fuzzy system is designed using triangular and trapezoidal membership functions with the center average defuzzifier and singleton fuzzifier to regulate the LQR gains for each degree of freedom because of the uncertainties and nonlinearities. Then, the fuzzy system is optimized using MOHEPSO to find the best slopes for the membership functions with regard to minimization of the errors and control efforts. Finally, the obtained results are presented for a nonlinear 4DOF multi-purpose (for marine, ground and aerial maneuvers) quadrotor system designed and fabricated in Sirjan University of Technology, Sirjan, Iran, to assure the effectiveness of the proposed approach. (C) 2019 Elsevier Masson SAS. All rights reserved.
机译：本文提出了一种基于线性二次调节器（LQR）方法的鲁棒模糊控制器，并通过多目标高探测粒子群优化（MOHEPSO）对非线性四自由度（DOF）四旋翼飞机进行了优化。在通过雅可比矩阵进行线性化之后，将应用LQR方法。模糊系统是使用三角形和梯形隶属度函数以及中心平均解模糊器和单例模糊器来设计的，由于不确定性和非线性，它们会针对每个自由度调节LQR增益。然后，使用MOHEPSO对模糊系统进行优化，以针对误差最小化和控制效果找到隶属函数的最佳斜率。最后，为非线性四自由度多用途（海洋，地面和空中机动）四旋翼系统提供了获得的结果，该系统是在伊朗锡尔詹工业大学设计和制造的，以确保所提出方法的有效性。 （C）2019 Elsevier Masson SAS。版权所有。

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