The data-based LQG control problem Conference Paper uri icon


  • We define a data-based controller as one that can be synthesized using only knowledge of the plant input-output data, requiring neither a state space model nor a transfer function of the plant. In this paper the data-based LQG control problem is formulated and solved. Given finite Markov parameter data sequences (which can be computed from almost any input-output data) between the input-output and noise-output, the problem of data-based LQG control is to find the optimal control sequence which minimizes the quadratic cost function over some finite interval [0, N]. We show that a state space model is not necessary for this problem. Rather a finite sequence of input-output data is required to compute a finite set of Markov parameters. This data can be computed off-line, or on-line, on the previous control period [0, N] to prepare for a subsequent period [N, 2N]. A numerical example is given to illustrate the effectiveness of the data-based control theory.

name of conference

  • Proceedings of 1994 33rd IEEE Conference on Decision and Control

published proceedings

  • Proceedings of 1994 33rd IEEE Conference on Decision and Control
  • Proceedings of the IEEE Conference on Decision and Control

author list (cited authors)

  • Skelton, R. E., & Shi, G.

citation count

  • 31

complete list of authors

  • Skelton, RE||Shi, Guojun

publication date

  • January 1994