Abstract
Time-varying recursive Riccati equations are exploited for a globally convergent discrete-time adaptive regulator for a fixed but unknown plant. With the addition of sufficiently rich perturbations for consistent parameter estimation, the controller is asymptotically the optimal regulator in a linear, quadratic Gaussian (LQG) sense with external perturbation signals.The scheme has advantages over globally convergent minimum variance based schemes in that there is a more direct trade-off between control energy and tracking error. For nonminimum phase plants, the scheme has an advantage of computational simplicity over globally convergent schemes based on solving Bezoutian equations for pole assignment, in that the Riccati equation is easier to update at each iteration than the solution of a Bezout equation.
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