Dynamic optimal control of heat-supply production process

According to the production actuality of thermodynamic industry, this paper makes heat-exchange process of heat-supply production the subject, integrates measurement technology, information fusion technology, computer technology, control technology, and fault diagnosis technology organically, and completely creates a network intelligent heat-exchange station, which can substitutes and is better than the one operated by man. It brings forward a method that RBF neural network applying soft-sensing technology picks up characteristic parameters of production process. It also brings forward a Fletcher&Reeves conjugated gradient method optimum model. All of these can bring guarantee for the realization of minimal parameter fuzzy fault diagnosis and measurement and control flat. The production processes of flow industry (such as electricity, chemical industry, heat industry, medicine and building) look like each other, so using RBF to pick up characteristic parameters is a good method to improve the stability of production process and product quality.