States Estimation And Optimization Of Batch Cooling Crystallization Process Of L-glutamic Acid

Crystallization is one of the main ways to extract products in the chemical production process,and the quality of crystals obtained through crystallization affects downstream production.The thesis mainly studies the state estimation algorithm and operating condition optimization of L-glutamic acid cooling crystallization process,the purpose is to improve the production efficiency of L-glutamic acid batch production process and the quality of crystal products.The model studied is the particle balance model(PBM).In order to facilitate the solution of the model,the quadrature method of moment(QMOM)is used to simplify the mechanism model.The final research model is the PBM in the form of moments.Aiming at the PBM form of moments,an augmented quadrature method of moments(AQMOM)is proposed to improve the efficiency of numerical solution.Aiming at the problem that the crystal size distribution(CSD)of the crystallization process is difficult to measure in real time,a nonlinear state estimator is designed.Using the real-time measurement value of the solution concentration in the crystallization process,combined with the moment model,an improved rolling time domain state estimation algorithm with variable time domain length is proposed to obtain the moment information of the CSD in the crystallization process.By applying the algorithm to a non-isothermal chemically stirred tank reaction process case and the size-dependent growth-nucleation process simulation case of L-glutamic acid crystals(nominal conditions and uncertain conditions),the state estimation proposed in this paper is verified and explained.Compared with the extended Kalman filter(EKF)and moving horizon estimator(MHE),the algorithm has better estimation accuracy and robustness.Aiming at the optimization problem of operating variables in the cooling crystallization process of L-glutamic acid,the Mayer index in the optimal control theory is used to design the objective function,and the optimal operating conditions are determined by solving the objective function.Based on the crystallization process moment model,the desired crystal product CSD is converted into the desired CSD moment.Different objective functions are defined for the pure crystal growth process and the growth nucleation process,and the corresponding operating condition optimization algorithm is established.The simulation results show that,compared with the linear and program cooling strategies commonly used in engineering,the optimized cooling strategy proposed in this paper can make the crystal grow to the desired CSD and significantly shorten the operation time of the crystallization process,making the crystal growth more concentrated.Finally,using the L-glutamic acid cooling crystallization experimental platform,the proposed operating condition optimization strategy was experimentally verified,and compared with the linear cooling strategy and the program cooling strategy.A particle analyzer(FBRM)was used to detect the size distribution of the crystal product.Experimental results show that the proposed optimization method can improve the quality of L-glutamic acid crystal products and significantly shorten the batch time of cooling crystallization process.