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In this Chapter, a closed-loopIterative Learning Control (ILC)ILCClosed-loop ILC scheme with dynamic output feedbackDynamic output feedback (DOF) is presented for industrial batch processesBatch process subject to time-varyingTime-varying uncertainties and nonrepetitive disturbances. Based on a 2D system description for the batch operation, anLinear Matrix Inequality (LMI) LMI-based sufficient condition is derived to guarantee theRobust convergencerobust convergenceConvergenceof the resulting ILCIterative Learning Control (ILC) system along both the time and batch directions, which could be effectively solved to determine the learning controller gains. Concerning the finite-frequency nature of load disturbanceLoad disturbancein engineering practice, anotherStatic output feedbackstatic output feedbackOutput feedback(SOF) based ILCIterative Learning Control (ILC) design with a finite-frequency-rangeFinite-frequency-range 2D \({\mathcal{H}}_{\infty}\) performance specificationPerformance specification is also presented for the convenience of implementation. Based on a 2D system description, sufficient conditions in terms ofNonlinear matrix inequality nonlinear matrix inequalities (NLMIs) are established to guarantee robust stabilityRobust stabilityof the resulting ILCIterative Learning Control (ILC) system along both the time and batch directions, by using the matrix dilatation technique. A two-stage heuristic approach is subsequently developed to derive the feasible ILCIterative Learning Control (ILC) controller gains, based on predesigning the correspondingState feedback state feedback (SF) based ILC gains for iterative computation. An illustrative example of the injection moldingInjection molding process is adopted to validate the effectiveness and advantages of the proposed ILC designs.

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Closed-Loop ILC Scheme with Output Feedback

  • 章节

  • 发表日期：

    2026年

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  • Tao Liu,
  • Shoulin Hao,
  • Youqing Wang,
  • Dewei Li

摘要

In this Chapter, a closed-loopIterative Learning Control (ILC)ILCClosed-loop ILC scheme with dynamic output feedbackDynamic output feedback (DOF) is presented for industrial batch processesBatch process subject to time-varyingTime-varying uncertainties and nonrepetitive disturbances. Based on a 2D system description for the batch operation, anLinear Matrix Inequality (LMI) LMI-based sufficient condition is derived to guarantee theRobust convergencerobust convergenceConvergenceof the resulting ILCIterative Learning Control (ILC) system along both the time and batch directions, which could be effectively solved to determine the learning controller gains. Concerning the finite-frequency nature of load disturbanceLoad disturbancein engineering practice, anotherStatic output feedbackstatic output feedbackOutput feedback(SOF) based ILCIterative Learning Control (ILC) design with a finite-frequency-rangeFinite-frequency-range 2D \({\mathcal{H}}_{\infty}\) performance specificationPerformance specification is also presented for the convenience of implementation. Based on a 2D system description, sufficient conditions in terms ofNonlinear matrix inequality nonlinear matrix inequalities (NLMIs) are established to guarantee robust stabilityRobust stabilityof the resulting ILCIterative Learning Control (ILC) system along both the time and batch directions, by using the matrix dilatation technique. A two-stage heuristic approach is subsequently developed to derive the feasible ILCIterative Learning Control (ILC) controller gains, based on predesigning the correspondingState feedback state feedback (SF) based ILC gains for iterative computation. An illustrative example of the injection moldingInjection molding process is adopted to validate the effectiveness and advantages of the proposed ILC designs.