Iterative LQG Controller Design Through Closed-Loop Identification

[+] Author and Article Information
Min-Hung Hsiao

Department of Mechanical Engineering, Taipei Institute of Technology, Taiwan

Jen-Kuang Huang

Dept. of Mechanical Engineering, Old Dominion University, Norfolk, VA 23529-0247

David E. Cox

Guidance and Control Branch, Flight Dynamics and Control Division, NASA Langley Research Center, Hampton, VA 23681-0001

J. Dyn. Sys., Meas., Control 118(2), 366-372 (Jun 01, 1996) (7 pages) doi:10.1115/1.2802331 History: Received April 02, 1994; Online December 03, 2007


This paper presents an iterative LQG controller design approach for a linear stochastic system with an uncertain openloop model and unknown noise statistics. This approach consists of closed-loop identification and controller redesign cycles. In each cycle, the closed-loop identification method is used to identify an open-loop model and a steady-state Kalman filter gain from closed-loop input/output test data obtained by using a feedback LQG controller designed from the previous cycle. Then the identified open-loop model is used to redesign the state feedback. The state feedback and the identified Kalman filter gain are used to form an updated LQG controller for the next cycle. This iterative process continues until the updated controller converges. The proposed controller design is demonstrated by numerical simulations and experiments on a highly unstable large-gap magnetic suspension system.

Copyright © 1996 by The American Society of Mechanical Engineers
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