Title :
LQR control of double inverted-pendulum based on genetic algorithm
Author_Institution :
Higher Vocational & Tech. Coll., Univ. of Sci. & Technol. Liaoning, Anshan, China
Abstract :
In practice, the key problem to apply LQR optimal control method is how to correctly choose the weighted matrix of performance index. At present, there is no formulaic approach for this problem. To obtain the satisfying results, people must repeat to test many times. This kind of LQR control method based on genetic algorithms, which can obtain satisfying control results at first hand, is presented for double inverted pendulum system. The method optimizes the Q-matrix by using genetic algorithms, selects trace of the result of Riccati equation as the objective function. The control problem of double inverted pendulum is resolved successfully. The simulation results prove that the control effect by this method is better than the other methods mentioned in the references.
Keywords :
Riccati equations; genetic algorithms; linear quadratic Gaussian control; matrix algebra; nonlinear control systems; pendulums; performance index; LQR control; LQR optimal control; Q-matrix; Riccati equation; double inverted pendulum system; genetic algorithm; objective function; performance index; weighted matrix; Automation; Genetic algorithms; Informatics; Materials; Mathematical model; Performance analysis; Suspensions; LQR; double inverted-pendulum; genetic algorithm;
Conference_Titel :
Intelligent Control and Automation (WCICA), 2011 9th World Congress on
Conference_Location :
Taipei
Print_ISBN :
978-1-61284-698-9
DOI :
10.1109/WCICA.2011.5970540