Stochastic adaptive control for exponentially convergent time-varying systems

This paper shows that the standard stochastic adaptive control algorithms for time-invariant systems have an inherent robustness property which renders them applicable, without modification, to time-varying systems whose parameters converge exponentially. One class of systems satisfying this requirement is those having non-steady-state Kalman filter or innovation representations. This allows the usual assumption of a stationary ARMAX representation to be replaced by a more general state space model.