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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

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Abstract 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… Click to show full abstract

Abstract 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.

Keywords: freedom; linear quadratic; optimized multi; degree freedom; quadratic regulator; robust fuzzy

Journal Title: Aerospace Science and Technology
Year Published: 2020

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