In this paper the Markov data-based LQG control problem is considered. The Markov data-based LQG control problem is to find the optimal control sequence which minimizes a quadratic cost function over some finite interval [0, N]. To solve this problem, we show that a complete input-output description of the system is not necessary. Obviously, a complete state space model is not necessary for this problem either. The main contributions of this paper include: (i) develop a new data-based LQG controller in a recursive form and a batch-form, (ii) derive a closed-form expression for the system’s optimal performance in terms of the Markov parameters, (iii) develop an algorithm for choosing the output weighting matrix, and (iv) demonstrate that the amount of information about the system required by the data-based controller design is less than the amount required to construct the full state space model. A numerical example is given to show the effectiveness of the data-based design method. [S0022-0434(00)02503-X]
Skip Nav Destination
Article navigation
September 2000
Technical Papers
Markov Data-Based LQG Control1
Guojun Shi, Senior Project Engineer,,
Guojun Shi, Senior Project Engineer,
General Motors Corporation, GM Powertrain, 3300 GM Road, MC 483-331-500, Milford, MI 48380
Search for other works by this author on:
Robert E. Skelton, Professor,
Robert E. Skelton, Professor,
Structural Systems and Control Lab, University of California at San Diego, Department of Applied Mechanics and Engineering Sciences, 9500 Gilman Dr., La Jolla, CA 92093-0411
Search for other works by this author on:
Guojun Shi, Senior Project Engineer,
General Motors Corporation, GM Powertrain, 3300 GM Road, MC 483-331-500, Milford, MI 48380
Robert E. Skelton, Professor,
Structural Systems and Control Lab, University of California at San Diego, Department of Applied Mechanics and Engineering Sciences, 9500 Gilman Dr., La Jolla, CA 92093-0411
Contributed by the Dynamic Systems and Control Division for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received by the Dynamic Systems and Control Division October 6, 1998. Associate Technical Editor: S. D. Fassois.
J. Dyn. Sys., Meas., Control. Sep 2000, 122(3): 551-559 (9 pages)
Published Online: October 6, 1998
Article history
Received:
October 6, 1998
Citation
Shi, G., and Skelton, R. E. (October 6, 1998). "Markov Data-Based LQG Control." ASME. J. Dyn. Sys., Meas., Control. September 2000; 122(3): 551–559. https://doi.org/10.1115/1.1286868
Download citation file:
Get Email Alerts
Vibration Suppression Based on Improved Adaptive Optimal Arbitrary-Time-Delay Input Shaping
J. Dyn. Sys., Meas., Control (May 2025)
Robust Fault Detection for Unmanned Aerial Vehicles Subject to Denial-of-Service Attacks
J. Dyn. Sys., Meas., Control
Vibration Suppression and Trajectory Tracking with Nonlinear Model Predictive Control for UAM Aircraft
J. Dyn. Sys., Meas., Control
Learning battery model parameter dynamics from data with recursive Gaussian process regression
J. Dyn. Sys., Meas., Control
Related Articles
Stochastic Finite-Time Stabilization for a Class of Nonlinear Markovian Jump Stochastic Systems With Impulsive Effects
J. Dyn. Sys., Meas., Control (April,2015)
Probabilistic Control for Uncertain Systems
J. Dyn. Sys., Meas., Control (March,2012)
Marginal Instability and Intermittency in Stochastic Systems—Part II: Systems With Rapid Random Variations in Parameters
J. Appl. Mech (May,2009)
Global Path-Following Control of Stochastic Underactuated Ships: A Level Curve Approach
J. Dyn. Sys., Meas., Control (July,2015)
Related Proceedings Papers
Related Chapters
QP Based Encoder Feedback Control
Robot Manipulator Redundancy Resolution
Stability for a Class of Infinite Dimension Stochastic Systems with Delay
International Conference on Computer Technology and Development, 3rd (ICCTD 2011)
Norms of Feedback Systems
Robust Control: Youla Parameterization Approach