Title :
A discrete-time learning control algorithm for a class of linear time-invariant systems
Author_Institution :
Union Switch & Signal, Pittsburgh, PA, USA
fDate :
6/1/1995 12:00:00 AM
Abstract :
A discretized version of the D-type learning control algorithm is presented for a MIMO linear discrete-time system. A necessary and sufficient condition for uniform convergence of the proposed learning algorithm is presented. Then, we prove that the same condition is sufficient for the global robustness of the proposed learning algorithm to state disturbances, measurement noise at the output, and reinitialization error are present at each iteration. A numerical example is given to illustrate the results
Keywords :
MIMO systems; discrete time systems; learning systems; multivariable control systems; robust control; stability criteria; D-type learning control algorithm; MIMO linear discrete-time system; discrete-time learning control algorithm; global robustness; iteration; linear time-invariant systems; measurement noise; necessary and sufficient condition; reinitialization error; state disturbances; uniform convergence; Control systems; Convergence; MIMO; Noise measurement; Noise robustness; Nonlinear control systems; Robust control; Sufficient conditions; Switches; Vectors;
Journal_Title :
Automatic Control, IEEE Transactions on