论文标题
基于ARX模型的嵌入线性MPC的无构造坐标增强拉格朗日方法
A construction-free coordinate-descent augmented-Lagrangian method for embedded linear MPC based on ARX models
论文作者
论文摘要
本文提出了一种无构造算法，用于解决基于外源性术语（ARX）输入输出模型的自回旋的线性MPC问题。解决方案算法依赖于先前提出的坐标呈凝分呈凝分的增强拉格朗日（CDAL）方法，我们在此处适应了基于ARX的MPC的特殊结构。 CDAL-ARX算法享有无构造功能，因为它避免了与MPC相关的二次编程（QP）问题明确构建二次编程（QP）问题，当ARX模型在线更改/适应时，这将消除施工成本。例如，ARX模型参数取决于线性参数变化（LPV）调度信号，或者递归根据廉价的计算成本从流式输入输入数据进行调整，这使ARX模型广泛用于自适应控制。此外，由此产生的CDAL-ARX算法的实现是无基质的且不含库的，因此可以在工业嵌入式平台中部署。我们在两个数值示例中显示了CDAL-ARX的效率，还与基于其他通用二次编程求解器的MPC实现相比。
This paper proposes a construction-free algorithm for solving linear MPC problems based on autoregressive with exogenous terms (ARX) input-output models. The solution algorithm relies on a coordinate-descent augmented Lagrangian (CDAL) method previously proposed by the authors, which we adapt here to exploit the special structure of ARX-based MPC. The CDAL-ARX algorithm enjoys the construction-free feature, in that it avoids explicitly constructing the quadratic programming (QP) problem associated with MPC, which would eliminate construction cost when the ARX model changes/adapts online. For example, the ARX model parameters are dependent on linear parameter-varying (LPV) scheduling signals, or recursively adapted from streaming input-output data with cheap computation cost, which make the ARX model widely used in adaptive control. Moreover, the implementation of the resulting CDAL-ARX algorithm is matrix-free and library-free, and hence amenable for deployment in industrial embedded platforms. We show the efficiency of CDAL-ARX in two numerical examples, also in comparison with MPC implementations based on other general-purpose quadratic programming solvers.
