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Research On Robust Predictive Control Method Based On Extended State Space Model

Posted on:2021-04-27Degree:MasterType:Thesis
Country:ChinaCandidate:Z H WuFull Text:PDF
GTID:2428330647963750Subject:Control theory and control engineering
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In actual industrial production,the controlled object is inevitably affected by unfavorable factors such as uncertainty,external disturbances and input and output constraints between the control systems caused by changes in the external environment and improper human operation,which may cause the system to fail to track the setting value may even cause unstable system operation.Therefore,how to ensure that the system can effectively track the set value of the controlled object while achieving optimal control is an important problem that still needs to be solved in modern industry.This dissertation is devoted to studying the shortcomings of the above industrial process control methods,and proposes a robust predictive control method based on the extended state space model.In this dissertation,firstly,the discrete system with uncertainty and unknown interference is expressed in the form of state space,and the output error is extended into the model,thereby forming a new extended state space model with less conservatism.The system control law designed based on this model can eliminate the steady-state error while adjusting the dynamic response of the system state and the output tracking error.Secondly,on the basis of the feasibility of the extended state space model,considering that the actual industry system has input and output constraints and time-varying setpoint tracking,this dissertation proposes to extend the time-varying setpoint tracking problem to the newly designed state model in the space solution,the controller designed based on this model can track the set values required by the system online,providing more adjustable degrees of freedom for the system controller.In addition,by constraining the upper limit of the input and output problems,the Lyapunov function of the difference equation is constructed to solve the sufficient conditions to ensure the stability of the closed-loop system of the linear matrix inequality(LMI),and the LMI is solved online to obtain the control law of the system.Finally,simulation is used to verify the effectiveness and feasibility of the design method in this dissertation.Simulation results show that the robust predictive control method of the extended state space model successfully achieves the optimization of the control performance of the system,tracking the time-varying setpoints of the upper system and increasing the freedom of controller design.This is a good application value.
Keywords/Search Tags:Robust Model Predictive Control(RMPC), system uncertainty, outside disturbance, input and output constraints, time-varying setpoint tracking
PDF Full Text Request
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