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Content archived on 2024-05-14

Computer integrated design of industrial control

Objective



To maintain the competitive edge of European industry it is essential that quality and productivity are maximised in manufacturing. For most processes this means that advanced control should be used which integrates quality assurance and economic efficiency. Model Based Preditive Control (MBPC) has been shown in many real systems to provide such integration and can often give a pay back time on capital expenditure of less than a year. The Working Group believes that a sustained campaign to spread the benefits of MBPC will be of great significance.

The installation of MBPC requires skills not generally found in industry, as control design traditionally has been at a low level. The inclusion of economic and quality factors (ISO 9000) into an integrated control scheme requires planning and cooperation between control technologists, process engineers, and management. It is important to provide demonstrators of the technology and mechanisms by which the economic benefits can be assessed before installing any MBPC system.

The crucial step of MBPC is the acquisition of a process model which is used to provide predictions of the effects of hypothesised control actions. Sometimes the most appropriate model is a black box model or even a qualitative model. Often the model is not accurate over the whole operating region of the process, and it is vital to research methods which provide robust models (particularly in non-traditional areas) and MBPC designs which are still effective despite inevitable modelling errors.

Most industrial processes involve constraints : for example torque saturation in robotic actuators or temperature limits in a catalytic cracker. It is generally found that the best economic operation of a process is near or on a constraint boundary. MBPC is the only modern control approach which can handle constraints as a natural part of the algorithm. However, the use of constraints imposes several burdens on the optimization algorithm : computational load (significant for fast processes) ; lack of feasilibility (for over constrained systems) : potential instability (for particular types of process dynamics). The best way in which to deal with these problems is a matter for urgent research.

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ACM - Preparatory, accompanying and support measures

Coordinator

Association pour le Développement de l'Enseignement et de la Recherche en Système Appliqué
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7 boulevard du Maréchal Juin
91371 Verrières-le-Buisson
France

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