A QUALITATIVE APPROACH TO MODEL-REFERENCE ADAPTIVE-CONTROL (QMRAC)

This paper proposes a new approach for utilizing qualitative simulatio n techniques within a model reference adaptive system for the control of ill-defined and uncertain processes, typical of the process industr ies. It is argued that the practical specification of performance of i ndustrial systems is very often imprecise and multi-valued leading to non-unique (numerical) descriptions of the reference behaviour and, fu rther, that the lack of precise knowledge of the industrial process re sults in inaccurate (numerical) models of the process to be controlled . This can lead to significant deterioration in performance with respe ct to the desired specification necessitating empirical tuning and hen ce the loss of analytic properties. Qualitative simulation techniques are used to model imprecise specifications and process knowledge, and hence to generate the reference behaviour without a loss of accuracy w ith respect to the original specifications. The discrepancy between th e actual and the reference behaviour is used to adapt a conventional c ontrol algorithm such that model-following behaviour is maintained in the face of significant disturbance to the normal behaviour. Results a re presented for first- and second-order models of desired specificati ons. The results are very encouraging, demonstrating that accurate ada ptive behaviour of ill-defined systems can be obtained without the nee d to corrupt. or approximate, the original specifications, and without necessitating the availability of accurate, high-order, numerical mod els. (C) 1998 Elsevier Science Ltd. All rights reserved.