DocumentCode
2736132
Title
LQG optimum controller design and simulation base on inter model control theory
Author
Jin, Qi-bing ; Ren, Shi-bing ; Quan, Ling
Author_Institution
Autom. Res. Inst., Beijing Univ. of Chem. Technol., Beijing, China
Volume
3
fYear
2009
fDate
20-22 Nov. 2009
Firstpage
62
Lastpage
65
Abstract
Base on the traditional internal model control(IMC) principle, the linear quadric Gauss optimal control(LQG) was adopted into the IMC construct in this article. Considering system random noise and measurement noise, based on the system performance index, the process model state feedback controller(LQ) and Kalman filter was designed, Thus the system controller is LQG controller which consist of LQ with Kalman filter and IMC controller, and has the advantages of LQG optimum control and tradition IMC. The simulation shows that this new method can overcome the influence of the parameter variation and system noise of the controlled object with time delay on control performance, and has strong robustness and good stability. In addition, the proposed method is easy to regulate, and it is fit for engineering applications.
Keywords
Kalman filters; control system synthesis; linear quadratic Gaussian control; optimal control; performance index; random noise; robust control; state feedback; Kalman filter; LQG optimum controller design; inter model control theory; internal model control principle; linear quadric Gauss optimal control; measurement noise; parameter variation; process model state feedback controller; random noise; robustness; system controller; system noise; system performance index; time delay; Control system synthesis; Control theory; Delay effects; Gaussian processes; Noise measurement; Noise robustness; Optimal control; Robust stability; State feedback; System performance; Correction controller; IMC; Kalman filter; LQG optimum control; Simulation; component;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Computing and Intelligent Systems, 2009. ICIS 2009. IEEE International Conference on
Conference_Location
Shanghai
Print_ISBN
978-1-4244-4754-1
Electronic_ISBN
978-1-4244-4738-1
Type
conf
DOI
10.1109/ICICISYS.2009.5358234
Filename
5358234
Link To Document