Journal article
Ü. Önen, Abdullah Çakan, I. Ilhan
Turkish J. Electr. Eng. Comput. Sci., 2019
Turkish J. Electr. Eng. Comput. Sci., 2019
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APA
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Önen, Ü., Çakan, A., & Ilhan, I. (2019). Performance comparison of optimization algorithms in LQR controller design fora nonlinear system. Turkish J. Electr. Eng. Comput. Sci.
Chicago/Turabian
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Önen, Ü., Abdullah Çakan, and I. Ilhan. “Performance Comparison of Optimization Algorithms in LQR Controller Design Fora Nonlinear System.” Turkish J. Electr. Eng. Comput. Sci. (2019).
MLA
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Önen, Ü., et al. “Performance Comparison of Optimization Algorithms in LQR Controller Design Fora Nonlinear System.” Turkish J. Electr. Eng. Comput. Sci., 2019.
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@article{ue2019a,
title = {Performance comparison of optimization algorithms in LQR controller design fora nonlinear system},
year = {2019},
journal = {Turkish J. Electr. Eng. Comput. Sci.},
author = {Önen, Ü. and Çakan, Abdullah and Ilhan, I.}
}
Abstract
The development and improvement of control techniques has attracted many researchers for many years. Especially in the controller design of complex and nonlinear systems, various methods have been proposed to determine the ideal control parameters. One of the most common and effective of these methods is determining the controller parameters with optimization algorithms.In this study, LQR controller design was implemented for position control of the double inverted pendulum system on a cart. First of all, the equations of motion of the inverted pendulum system were obtained by using Lagrange formulation. These equations were linearized by Taylor series expansion around the equilibrium position to obtain the state-space model of the system. The LQR controller parameters required to control the inverted pendulum system were determined by using a trial and error method. The determined parameters were optimized by using five different configurations of three different optimization algorithms (GA, PSO, and ABC). The LQR controller parameters obtained as a result of the optimization study with five different configurations of each algorithm were applied to the system and the obtained results were compared with each other. In addition, the configurations that yielded the best control results for each algorithm were compared with each other and the control results were evaluated in terms of response speed and response smoothness.
