Simultaneous identification and adaptive control of unknown systems over finite parameter sets Academic Article uri icon


  • The problem considered is one of simultaneously identifying an unknown system while adequately controlling it The system can be any fairly general discrete-time system and the cost criterion can be either of a discounted type or of a long-term average type, the chief restriction being that the unknown parameter lies in a finite parameter set. For a previously introduced scheme of identification and control based on biased maximum likelihood estimates, it is shown that 1) every Cesaro-limit point of the parameter estimates is closed-loop equivalent to the unknown parameter; 2) for both the discounted and long-term average cost criteria, the adaptive control law Cesaro-converges to the set of optimal control laws; and 3) in the case of the long-term average cost criterion, the actual cost incurred by the use of the adaptive controller is optimal and cannot be bettered even if one knew the value of the unknown parameter at the start. Copyright 1983 by The Institute of Electrical and Electronics Engineers, Inc.

published proceedings

  • IEEE Transactions on Automatic Control

author list (cited authors)

  • Kumar, P.

citation count

  • 22

complete list of authors

  • Kumar, P

publication date

  • January 1983