Title :
Block partial derivative and its application to neural-net-based direct model-reference adaptive control
Author_Institution :
Dept. of Electr. & Comput. Eng., Michigan Univ., Dearborn, MI, USA
fDate :
9/1/1994 12:00:00 AM
Abstract :
The concept of block partial derivative and the associated algebra are introduced. The algebra is then applied to direct-model-reference adaptive control (MRAC) of discrete-time nonlinear plants. Three MRAC algorithms are developed employing identification of the forward model, extended MIT rule and extended SPR rule. Local-convergence properties and results of simulation study are presented
Keywords :
adaptive control; algebra; control system analysis; convergence; discrete time systems; identification; model reference adaptive control systems; neural nets; nonlinear control systems; MRAC algorithms; algebra; block partial derivative; direct model-reference adaptive control; discrete-time nonlinear plants; extended MIT rule; extended SPR rule; forward model; identification; local-convergence; neural net based control;
Journal_Title :
Control Theory and Applications, IEE Proceedings -
DOI :
10.1049/ip-cta:19941395
