Research on Optimization and Control of Calcination Process in Soda Manufacture
|Course||Control Theory and Control Engineering|
|Keywords||Soda ash calcined Dynamic Matrix Control Intelligent Control Optimal Load|
When change for the soda ash calcination process, the complex process characteristics of large delay, multivariate strong coupling, single calciner predictive control based on the MPC optimal control strategies based on economic indicators optimized calcination process, and further for The the actual calcination multiple the calciner parallel run of the production process for the production load change smart MPC optimal control strategy. The research work includes: brief soda ash the calcination process technology and equipment development process, focusing on analysis of the process principle of the calcination process control features, summarizes the domestic and international soda ash calcination process control strategy research and application status. Industrial site investigation and analysis of process data on soda ash calcination process control indicators, and study the principles and characteristics of a the conventional soda ash calcination process control strategy, analysis of the main problems in the conventional control strategy implementation and on the basis of the need for the implementation of advanced control in the calcination process. Dynamic model for the the calciner single soda ash calcination process optimization objectives multivariate DMC optimize control strategies used in the calcination process and through MATLAB simulation validation. The simulation results show that the optimal control strategy can be a key process indicators alkali temperature, outlet temperature is maintained within the normal range, to ensure product quality, achieve better control effect. Then, on the basis of the above-mentioned control strategy based on economic indicators optimized multi-variable model predictive control to optimize control strategies, rolling optimization to minimize economic indicators steady-state optimization and dynamic optimization, simulation results show that the optimal control strategy can not only achieve the calcination process control and optimization of key process indicators, to ensure product quality, but also to achieve \4, analysis of various process conditions encountered in industrial field, for actual industrial field of multiple the calciner parallel work control and optimization problems, the single the calciner multivariate model predictive control based on the combination of fuzzy control, expert control strategy , proposed a production conditions change dynamically allocated intelligent MPC wet weight alkali feed rate optimization control strategy. The simulation results show that the optimal control strategy in support of fault diagnosis and monitoring of furnace conditions can dynamically allocated according to the calciner conditions into the amount of the base, under the premise of ensuring product quality, to achieve overall optimization of the alkali content of the total input. Finally, the optimized control strategy applied to a soda ash plant light gray calcination process project achieved good control effect.