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 technique indices that are closely related to the improved product quality, enhanced production efficiency and reduced consumption.As a result, the optimal control for the technique indices has attracted an increased attention of various process industries.
The optimal control of the technique indices requires an optimal combination of technique indices and the operation of each control loops. In this paper, a hybrid intelligent control consisting of two layers, namely the optimal control of technique indices and the intelligent process control, is proposed for process industries. The optimal control of technique indices consists of the optimally selected set points of each 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 technique indices into a required number of setpoints for each control loops. When either operating point changes or the system is subjected to unexpected disturbances, the control loop can be made to follow the updated setpoints so that the technique indices can be controlled into their targeted ranges, leading to an optimization of the technique indices.
The proposed system has been successfully applied to the largest hematite minerals processing production line in China, where remarkable social and economic benefits have been achieved. Such an industrial application has demonstrated the performance of the proposed optimal control method and will have potentials for further and much wider applications.