Predictor Based Temperature Control And Batch Optimization For Crystallization Reactors

Time delay response is prevalent in chemical production processes.In recent years,many scholars in the field of control engineering have studied and discussed how to overcome the adverse effect of time delay to improve the performance of control systems.In this thesis,an predictor-based control structure is proposed for open-loop stable and integrating process with input or output time delay,and then an predictor-based temperature control system design and batch optimization scheme are given for the crystallization reactor.The main research contents include:A novel predictor-based disturbance rejection control scheme is proposed for open-loop stable and integrating processes with time delay.First,a generalized predictor(GP)and two realizable differentiators with finite gain are utilized to estimate the delay-free output response and its variation characteristics,and then the disturbance response is predicted for feedforward compensation based on the input signal and the delay-free output response estimation.By specifying the desired closed-loop poles,the feedback controller is derived backwards.A prominent advantage of the proposed method lies in that a trade-off between the control performance and its robustness against process uncertainties can be made conveniently by monotonically tuning the single adjustable parameters in the prediction filter,differentiator and feedback controller,respectively.The sufficient condition for robust stability of the closed-loop system is analyzed based on the small gain theorem.Two illustrative examples from the recent literature are adopted to demonstrate the effectiveness and superiority of the proposed control scheme.A predictive extended state observer(PESO)based indirect-type iterative learning control(ILC)is proposed for the operation optimization of batch process with time delay response.By leveraging the simplified generalized predictor(SGP)to predict the delay-free system output,a PESO based feedback control in the closed-loop control structure is designed to overcome the adverse effect of nonrepetitive uncertainties and disturbances.Then,a proportional controller based indirect-type ILC updating law is adopted to optimize the control performance from batch to batch by only adjusting the set-point command of the resulting inner-loop control system.A delay-independent sufficient condition is established to guarantee the convergence of tracking error along the batch direction based on the double-dynamic analysis(DDA),and meanwhile a delay-dependent sufficient condition in terms of linear matrix inequalities(LMI)is given to assess robust stability of the designed ILC control system along both the time and batch directions.An Illustrative example from the literature is performed to demonstrate the effectiveness and advantages of the proposed control method.The ILC control scheme mentioned above is applied to the design of temperature control system for a 4-litre jacketed crystallization reactor,and the step response identification experiment of the temperature rise process are conducted to obtain an integrating process model with time delay paremeter.Based on this model,the PESO is designed and the parameter of the ILC is tuned,and an application method for determining the desired output reference trajectory is given.For batch optimization experiment of the reactor temperature rise process,a metric for evaluating the disturbance rejection performance is proposed to determine the optimal disturbance rejection performance of batch operation.The temperature control experiment results of the crystallization reactor demonstrate that the designed ILC method can significantly improve the batch control effect.