Study On Control Strategy Of Converter Gas Recovery Evaporative Cooler

Converter flue gas dry dust removal technology has the advantages of low dust emission and high gas recovery efficiency. Thus it has been widely used. But because the dust removal system of evaporative cooler control object has the characteristics of nonlinear, large delay, strong coupling, the conventional PID control is difficult to effective application. Therefore, carrying out the topic research has important engineering value.At first, the paper introduces the status of research and development of converter dry dedusting technology, on the analysis of the system process, based on the summarized the characteristics of evaporative cooler of flue gas temperature control process parameters, control system, the technical indicators are summarized. A nonlinear model predictive control method based on support vector regression is proposed, and its parameters are optimized by using a simplified particle swarm optimization algorithm. The specific work is as follows:1) In the analysis of the basic particle swarm optimization algorithm(particle swarm optimization, particle swarm optimization(PSO) is easy to fall into local optimum and searching and low precision, with small long-term decreasing inertia weight and increasing extreme perturbation operator, improved simplified particle swarm algorithm, improved particle swarm algorithm is used to find the optimum speed and accuracy, improve the computational efficiency of the algorithm.2) For nonlinear system modeling problem, consider nonlinear fitting ability of different algorithms, support vector regression algorithm is introduced, using the simplified particle swarm optimization the parameters of optimization, construction sPSO-SVR model predictive controller is and the single step and multi step model predictive control algorithm is simulated and compared.The results show that the controller has good control performance sPSO-SVR the multi step model prediction based on, can have effect for predictive control of nonlinear systems.3) For evaporation cooler objects have when degeneration and model parameters uncertainty features proposed sPSO-SVR the multi step model predictive control strategy of optimization control scheme based on using the algorithm of rolling optimization and feedback correction function and expand evaporative cooler outlet temperature of control research, on this basis,through the simulation of MATLAB to analyze and verify the effectiveness of the control method,and achieve the ideal control effect.4) Finally, the subject to Baosteel Meishan Steel Company the second steelmaking factory for250 t converter dry dedusting system for object by Siemens automation product design evaporative cooler control system of DCS(distributed control system), and the hardware configuration and selection, PLC system hardware configuration and STEP7 and WinCC software program development.