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Coupling MPC and HJB for the Computation of POD-Based Feedback Laws

机译:耦合MPC和HJB以计算基于POD的反馈法律

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In this paper we use a reference trajectory computed by a model predictive method to shrink the computational domain where we set the Hamilton-Jacobi Bellman (HJB) equation. Via a reduced-order approach based on proper orthogonal decomposition(POD), this procedure allows for an efficient computation of feedback laws for systems driven by parabolic equations. Some numerical examples illustrate the successful realization of the proposed strategy.
机译:在本文中,我们使用模型预测方法计算的参考轨迹来缩小我们设置Hamilton-Jacobi Bellman(HJB)方程的计算域。通过基于适当的正交分解(POD)的降低阶方法,该过程允许有效地计算由抛物线方程驱动的系统的反馈规律。一些数值示例说明了拟议策略的成功实现。

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