HYSTERESIS SWITCHING ADAPTIVE-CONTROL OF LINEAR-MULTIVARIABLE SYSTEMS

This paper presents a model reference adaptive control scheme for dete rministic continuous-time multivariable systems represented by square, strictly proper, minimum-phase transfer function matrices. A typical requirement of existing algorithms is to assume that the zero structur e at infinity and the high-frequency gain matrix are fully (or at leas t partially) known. It is well known that these requirements may be ve ry restrictive, since, in general, both the zero structure at infinity and the high-frequency gain matrix depend on plant parameters. In thi s paper we show that these restrictive assumptions may be considerably weakened using a hysteresis switching control strategy recently intro duced by Morse et al. [11]. The strategy entails running a finite numb er of parameter estimators in parallel and using a switching algorithm to select between candidate estimators based on their associated pred iction errors. Hysteresis in the switching algorithm precludes switchi ng arbitrarily rapidly between estimators, and all switching ceases wi thin a finite time. The results represent a significant step forward i n understanding the minimal amount of prior knowledge necessary to des ign a stabilizing controller for a linear multivariable system.