@article{Emakpo_Olarewaju_2023, title={Determination of Parameters of Linear Quadratic Regulator using Global Best Inertia Weight Modified Particle Swarm Optimization Algorithm}, volume={4}, url={https://scienpg.com/jea/index.php/jea/article/view/jea-2023-01-003}, DOI={10.38032/jea.2023.01.003}, abstractNote={<p>The characteristics of a linear Quadratic Regulator (LQR) are hinged upon two parameters and they are, the state weighting matrix Q and the Control weighting matrix R. In this study Global Best Inertia Weight modified variant of the particle swarm optimization algorithm was used to determine these two important parameters of an LQR which was then used to control a bus suspension system. The evaluation of the open loop and closed loop showed that the closed loop system attained a steady state in a time of 350.36 seconds compared to the open loop system (47,734.3 seconds) when both systems were subjected to pot hole (step) signal.</p>}, number={01}, journal={Journal of Engineering Advancements}, author={Emakpo, Agbroko Oghenenyoreme and Olarewaju, Ogunti Erastus}, year={2023}, month={Mar.}, pages={14–18} }