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An economic MPC formulation with offset-free asymptotic performance

机译:具有无偏移渐近性能的经济型MPC公式

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This paper proposes a novel formulation of economic MPC for nonlinear discrete-time systems that is able to drive the closed-loop system to the (unknown) optimal equilibrium, despite the presence of plant/model mismatch. The proposed algorithm takes advantage of: (i) an augmented system model which includes integrating disturbance states as commonly used in offset-free tracking MPC; (ii) a modifier-adaptation strategy to correct the asymptotic equilibrium reached by the closed-loop system. It is shown that, whenever convergence occurs, the reached equilibrium is the true optimal one achievable by the plant. An example of a CSTR is used to show the superior performance with respect to conventional economic MPC and a previously proposed offset-free MPC still based on a tracking cost. The implementation of this offset-free economic MPC requires knowledge of plant input-output steady-state map gradient, which is generally not available. To this aim a simple linear identification procedure is explored numerically for the CSTR example, showing that convergence to a neighborhood of the optimal equilibrium is possible.
机译:本文提出了一种针对非线性离散时间系统的经济型MPC的新颖公式,尽管存在工厂/模型不匹配的情况,该新颖的公式仍能够驱动闭环系统达到(未知)最佳平衡。所提出的算法利用了以下优点:(i)扩展系统模型,该模型包括集成无偏移跟踪MPC中常用的干扰状态; (ii)修正适应策略,以纠正闭环系统达到的渐近平衡。结果表明,无论何时发生收敛,达到的平衡都是植物可以达到的真正的最佳平衡。 CSTR的示例用于显示相对于传统的经济型MPC和仍然基于跟踪成本的先前提出的无偏移MPC的优越性能。这种无偏移的经济MPC的实施需要了解工厂投入产出稳态映射梯度,而这通常是不可用的。为了达到这个目标,对CSTR示例进行了简单的线性识别过程的数值研究,表明收敛到最佳平衡点附近是可能的。

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