Research On Robust Predictive Control Method Of Multiphase Batch Process With Time-varying Delay

A multi-phase batch process is an industrial process with the characteristics of easy product update,high added value,flexible operation and so on.Due to its complex characteristics such as time-varying time delay,asynchronous switching,and model nonlinearity,it brings certain difficulties to the smooth control and healthy operation of the entire production process.Therefore,the control problem of multi-phase batch process has received extensive attention from scientific researchers.In this paper,a more in-depth study of robust predictive control methods for multi-phase batch processes with time-varying time delays is carried out.The main contents are as follows:(1)Aiming at the multi-phase batch process with time-varying delay and partial actuator failure,a robust predictive switching control method is proposed.Firstly,according to the different phases of the multi-phase batch process,the corresponding sub-models are established,and the output tracking error is introduced into the state variables to establish a multidegree-of-freedom state space model.Secondly,using robust predictive control theory,Lyapunov stability theory,switched system theory,and modal dependent average residence time method,the sufficient conditions for stability based on the linear matrix inequality(LMI)constraint form are given to ensure that the system is asymptotically stable at each phase and exponentially stable in each batch.After that,solving the parameters in the corresponding LMI constraints,the average residence time and control law gain of each phase can be calculated.Finally,the injection and holding pressure phase of the injection molding process are taken as an example to carry out a simulation study.The simulation results show that the proposed method can ensure the stable operation of the injection molding process and realize the smooth switching between phases under the influence of timevarying delay,partial actuator failure and other factors.(2)Aiming at the unstable situation in the multi-phase batch process that the controller cannot follow the system state to switch in time,a robust predictive asynchronous switching control method is proposed.Firstly,the operating status of the multi-phase batch process is analyzed,and the multiphase batch process is described as a multi-phase equivalent model with stable and unstable subsystems.On this basis,the output tracking error is introduced,and the extended state space model is constructed to bring more degrees of freedom for subsequent controller design.Secondly,when designing the controller,considering that the set value will change continuously with the production requirements,the change of the set value is regarded as a bounded disturbance and H? performance index is introduced to improve the ability of the system to track the changed set value.Then,the sufficient conditions based on the LMI form to make the system asymptotically stable in each phase and exponentially stable in each batch are given.The calculation method of the minimum operating time of the stable condition and the longest operating time of the unstable condition in each phase are also given.These can avoid the emergence of asynchronous situations by using the idea of advanced switching.Finally,the injection molding process is simulated as an example.The simulation results prove that the proposed method can effectively avoid the instability in asynchronous switching and make the control system track the time-varying set value faster.(3)Aiming at the non-linear characteristics of the model in the multiphase batch process,a robust fuzzy predictive asynchronous switching control method is proposed.Firstly,the nonlinear multi-phase batch process is described as an equivalent closed-loop extended T-S model with stable and unstable subsystems according to fuzzy rules.Secondly,on the basis of the extended T-S model,a sufficient stability condition based on the LMI form is derived.By solving the parameters in the stability conditions,the control law of the corresponding sub model can be calculated,and the weight coefficient of each sub model and control law can be determined according to the current system state,so as to reduce the influence of model mismatch on the control performance of the traditional single point linearization model.In addition,in the design of the controller,considering the instability of the multi-phase batch process during switching,the mode-dependent average dwell time method is used to ensure that each phase of the control system is asymptotically stable and each batch index is stable.Next,the calculation methods for the shortest running time under stable conditions and the longest running time under unstable conditions are given.Finally,the simulation case verifies that the designed controller can effectively avoid the instability in switching and reduce the influence of the single-point linearization model on the control effect due to the model mismatch.