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<p>To address the problem of performance degradation of model predictive control (MPC) for discrete-time linear systems with input–output constraints caused by external disturbances and model-plant mismatch, an adaptive MPC method based on model parameters and external disturbances control compensation is proposed. This method combines the extended state observer (ESO) with the <InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(\Gamma \)</EquationSource> <EquationSource Format="MATHML"><math> <mi mathvariant="normal">Γ</mi> </math></EquationSource> </InlineEquation>-projection algorithm to simultaneously estimate external disturbances and model mismatch parameters. A control compensation strategy is then designed using these estimates to enhance tracking performance while respecting input and output constraints. Furthermore, the boundedness of parameter estimation errors is rigorously proved based on Lyapunov stability theory. Finally, the proposed control method is applied to the liquid level control of a desorption tower in the fluidized catalytic cracking (FCC) process. The simulation results show the effectiveness and superiority of the proposed method.</p>

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Adaptive MPC method based on control compensation for disturbance and model parameters

  • 期刊论文

  • 发表日期：

    2025年12月16日

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  • Haibo Zhu,
  • Jun Zhao,
  • Wei Wang

摘要

To address the problem of performance degradation of model predictive control (MPC) for discrete-time linear systems with input–output constraints caused by external disturbances and model-plant mismatch, an adaptive MPC method based on model parameters and external disturbances control compensation is proposed. This method combines the extended state observer (ESO) with the \(\Gamma \) Γ -projection algorithm to simultaneously estimate external disturbances and model mismatch parameters. A control compensation strategy is then designed using these estimates to enhance tracking performance while respecting input and output constraints. Furthermore, the boundedness of parameter estimation errors is rigorously proved based on Lyapunov stability theory. Finally, the proposed control method is applied to the liquid level control of a desorption tower in the fluidized catalytic cracking (FCC) process. The simulation results show the effectiveness and superiority of the proposed method.