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State estimation-based Model Predictive Controller (MPC) is gaining importance mainly because of its superior performance over conventional MPC. In this article, a Kalman Filter (KF) is used and state estimation based MPC for a Two Tank Interacting System (TTIS) is implemented, with detailed analysis on the qp.status of the MPC block in MATLAB Simulink. The study and analysis of qp.status of MPC block reveals, monitoring of qp.status can very well indicate whether MPC calculates an optimal control value by solving a Quadratic Programming (QP) problem. The novel contribution of the work is detection of MPC failure with the help of qp.status and use this signal information to switch to an alternate control action. In real time applications, qp.status of MPC block can be used to set an alarm or take any other suitable alternate control actions.

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Optimization Status Sensing and Failure Detection in MPC and Virtual Feedback MPC Applied to a Tank System

  • 会议论文

  • 发表日期：

    2026年

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  • Jothibasu Marappan,
  • Arun Kumar Pinagapani,
  • Geetha Mani,
  • Nithya Govindaraj,
  • Aadithya Anbumani

摘要

State estimation-based Model Predictive Controller (MPC) is gaining importance mainly because of its superior performance over conventional MPC. In this article, a Kalman Filter (KF) is used and state estimation based MPC for a Two Tank Interacting System (TTIS) is implemented, with detailed analysis on the qp.status of the MPC block in MATLAB Simulink. The study and analysis of qp.status of MPC block reveals, monitoring of qp.status can very well indicate whether MPC calculates an optimal control value by solving a Quadratic Programming (QP) problem. The novel contribution of the work is detection of MPC failure with the help of qp.status and use this signal information to switch to an alternate control action. In real time applications, qp.status of MPC block can be used to set an alarm or take any other suitable alternate control actions.