| In view of the industrial process usually subject to the characteristic of time delay,fault,multi-phase,uncertainties and unknown disturbance,the advanced control of industrial process brings about the huge challenge for the practical application.In this paper,from the linearity to the nonlinearity,from the fault free to the fault,from the single phase to multi-phase,taking the robust predictive control as main content,the robust predictive control methods for industrial processes with the time-varying delay based on LMI are studied by many theories such as,optimized control,H∞ control,linear matrix inequality,fuzzy control,stochastic control,switching system and mode-dependent average dwell time.The main work is as follows.(1)A delay-range-dependent robust constrained model predictive control is proposed for industrial process with uncertainties and unknown disturbances.The discrete-time linear system with the dynamic characteristic including uncertainties,unknown disturbance,state time-varying delay,input and output contains is expressed as the formation of state space and the output tracking error is extended into the state variables to form the new state space model with multi-degrees of freedom.The state feedback control law is designed based on this model.In order to obtain the control law,the novel,less conservative and more simplified delay-range-dependent stable conditions in terms of linear matrix inequality(LMI)are given.Meanwhile,the H∞ performance index is introduced in the stable derivation,which can reject any unknown bounded disturbances.On this basis,considering the industrial process with partial actuator failures,the robust constrained model predictive fault-tolerant control is studied.The fault-tolerant controller is designed by the extended state space model.LMI conditions are given by constructing Lyapunov-Krasovskii function based on the different inequality and combining the optimized performance index and H∞ performance index.The fault-tolerant control gain is obtained by solving LMI conditions.The simulation results on TTS20 tank system,multi-input and multi-output glasshouse process as well as the engineering application on the developed advance control system of the liquid level of TTS20 tank show that the proposed control method has better tracking performance and the rejection capability for the unknow disturbance rejection,uncertainties and actuator failures.(2)A robust fuzzy predictive control based on Takagi-Sugeno fuzzy(T-S)model is proposed for industrial process with time-varying delays,unknown disturbances as well as strong nonlinearity.Based on the idea of the fuzzy control theory,T-S fuzzy model is built by a number of linear sub-models in terms of each fuzzy rule and nonlinear membership functions to describe the above industrial process.Then this model is transformed into the equivalent T-S fuzzy model,the stability and robustness of system are studied by using the method of Lyapunov-Krasovskii function,the robust fuzzy predictive controller based on T-S fuzzy model is designed and the designed scheme is given.In the frame of the above study,considering the impact of the partial actuator failures on the system performance,the state feedback based fuzzy predictive fault-tolerant strategy is designed based on the parallel distributed compensation method and the extended T-S fuzzy model.A case study of continuous stirred tank reactor manifests that the proposed methods are effective and feasible.(3)A stochastic robust predictive fault-tolerant control approach is put forward for industrial process with interval time-varying delays and actuator failures occurring under a certain probability.The major contribution is that the robust predictive control method and the stochastic control theory are integrated to solve the problem of actuator failures satisfying some probability,which improves the traditional fault-tolerant control.The state space model with stochastic fault is established to describe a class of industrial processes with interval time-varying delays,uncertainties,unknown disturbances and actuator failures occurring under a certain probability and the stochastic fault-tolerant control strategy is designed by this model to switch to FTC control under the large probability of fault and to normal control under the small probability of fault,which can achieve the objective of energy conservation and consumption reduction.Based on this strategy,the related theorem and corollary in the form of LMI constraints are further given to solve the designed switching control law.The effectiveness and feasibility are verified by the case study of the tank system under the actuator failures with three difference probabilities.(4)A robust switched predictive control method is proposed for the multi-phase batch process with the time-varying delay,uncertainties and unknown disturbances.The switching model including the sub-model with the different dimension is established to describe the above dynamic performance of the multi-phase batch and then the robust switched predictive control law is designed by using the switching model.Making full use of Lyapunov function theory,switched system theory and mode-dependent average dwell time method,the sufficient conditions in terms of LMI constraints are derived to ensure that the switching system is asymptotically stable in each phase and exponentially stable in each batch.The control law gain and the average dwell time of each phase are thus calculated by solving these LMI constrains.Taking the switching process between the filling phase and pressure holding phase of the injection molding process as the research object,the simulation results show that the proposed method can make the controlled system stably and smoothly switch and ensure the minimum running time of each phase.In this way,the production efficiency of the batch process can be increased. |
