Title :
Design and performance analysis of adaptive linear quadratic Gaussian controller
Author :
Ezzaraa, M. ; Lafkih, M.A. ; Ramzi, M.
Author_Institution :
Electr. Eng. Dept., Univ. of Sultan Moulay Slimane, Beni-Mellal, Morocco
Abstract :
In this paper, the design process and performance analysis of Adaptive Linear Quadratic Gaussian (ALQG) control are presented. The controller is expected to control the speed of separately excited DC motor (SEDCM). Implement of this control law is performed trough the use of separation theorem, which involves the design of a Kalman estimator and a linear quadratic controller separately. A robust identification algorithm is used for the online estimation of a linear SISO model´s parameters. Simulation results show that the proposed controller has a remarkable performance for tracking reference trajectory while at the same time it is robust against noise imposed to system output.
Keywords :
DC motors; Kalman filters; adaptive control; angular velocity control; control system synthesis; linear quadratic Gaussian control; linear systems; parameter estimation; robust control; ALQG controller design process; ALQG controller performance analysis; Kalman estimator design; SEDCM speed control; adaptive linear quadratic Gaussian controller design process; adaptive linear quadratic Gaussian controller performance analysis; control law; online linear SISO model parameter estimation; reference trajectory tracking; robust identification algorithm; separately excited DC motor speed control; separation theorem; system output; Adaptation models; Argon; DC motors; Equations; Kalman filters; Mathematical model; Vectors; Adaptive Linear Quadratic Gaussian (ALQG); Kalman filtring; identification; separately excited DC motor (SEDCM);
Conference_Titel :
Complex Systems (ICCS), 2012 International Conference on
Conference_Location :
Agadir
Print_ISBN :
978-1-4673-4764-8
DOI :
10.1109/ICoCS.2012.6458554
