A hybrid intelligent optimal control method for the whole production line and applications

摘要

With ever increased needs for an improved product quality, production efficiency, and cost in today's globalized world market, advanced process control should not only realize the accuracy of each control loops, but also has the ability to achieve an optimization control of global production indices that are closely related to the improved product quality, enhanced production efficiency and reduced consumption. As a result, the optimal control for the global production indices has attracted an increased attention of various process industries. The optimal control of the global production indices requires an optimal combination of the production indices, technical indices and the operation of each control loops. In this paper, a hybrid intelligent control strategy is proposed for process industries. This new strategy consists of three control layers, namely the intelligent optimization of the global production indices, the intelligent optimal control of the technical indices and the intelligent process control,. The intelligent optimization of the global production indices is composed of the setting model of the technical indices, the predictor of the global production indices, the feedback and prediction analysis adjustment models. The intelligent optimal control of the technique indices consists of the setpoints model of control loops, the prediction of technical indices, the feedback and feedfoword regulators. The intelligent process control is then composed of normal decoupled PID controllers, decoupled nonlinear PID controllers with a neural network feedforword compersator for un-modeled dynamics and a switching mechanism. Such a control structure can automatically transfer the global production indices into a required number of setpoints for each control loops. Moreover, when the system is subjected to either operating point changes or unexpected disturbances, setpoints of the control loops can be adaptively updated and the outputs of the control loops are made to follow the updated setpoints so that the global production indices can be controlled into their targeted ranges to realize the optimization control of the global production indices. The proposed method has been successfully applied to the largest hematite minerals processing factory in China, where remarkable social and economic benefits have been achieved. Such an industrial application has successfully demonstrated the performance of the proposed optimal control method which will therefore has a high potential for further and much wider applications.