Multi-Objective Optimization of a Fuzzy Tracking Controller Using Differential Evolution for Nonlinear Three-Dimensional Tracking
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Abstract
The issue of three-dimensional tracking in a system involving nonlinear dynamics, couplings, uncertainties, and varying working conditions has become a challenge in current control engineering practice. It is of vital importance that in such a case, the precision of tracking is maximized while the control effort and energy consumed are minimized. In this paper, the optimized Fuzzy Logic Controller (FLC) has been designed for the three-dimensional tracking of a missile (satellite) through application of the Differential Evolution (DE) algorithm. The fuzzy membership function parameters are considered as design parameters, and the minimization of both the tracking error and energy is performed simultaneously as conflicting objectives. The parameters of the membership functions have been optimized through the use of the DE algorithm, and the performance of the controller has been enhanced. The results obtained through simulation prove that the fuzzy control based on DE yields an ideal compromise between tracking performance and energy utilization as compared to Proportional, Integral, and Derivative (PID) and Genetic Algorithm (GA)-based controllers in terms of overshoot and settling time. The proposed method serves as an efficient technique for the optimal design of fuzzy controllers for tracking problems in three-dimensional space.
Keywords
Fuzzy logic control Fuzzy controller Three-dimensional tracking Missile tracking Differential evolution Multi-objective optimization Genetic algorithmReferences (17)
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