Graham C. Goodwin, Peter Jeffrey Ramadge, Peter E. Caines

Research output: Contribution to journalConference articlepeer-review

9 Scopus citations


A description is given of recent results concerning global convergence of a stochastic adaptive control algorithm for discrete time linear systems. It is shown that, with probability one, the algorithm will ensure the system inputs and outputs are sample mean square bounded and the mean square output tracking error achieves its global minimum possible value for linear feedback control. Thus, asymptotically, the adaptive control algorithm achieves the same performance as could be achieved if the system parameters were known.

Original languageEnglish (US)
Pages (from-to)736-739
Number of pages4
JournalProceedings of the IEEE Conference on Decision and Control
StatePublished - Jan 1 1979
EventProc IEEE Conf Decis Control Incl Symp Adapt Processes 18th - Fort Lauderdale, FL, USA
Duration: Dec 12 1979Dec 14 1979

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

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