Block partial derivative and its application to neural-net-based direct model-reference adaptive control

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.