A Complexity Analysis of Event-Triggered Model Predictive Control on Industrial Hardware
A Complexity Analysis of Event-Triggered Model Predictive Control on Industrial Hardware
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DOI：
10.1109/tcst.2019.2938495
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发表时间：
2019-05
影响因子：
4.8
通讯作者：
Patrik Simon Berner;M. Mönnigmann
中科院分区：
文献类型：
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作者：
Patrik Simon Berner;M. Mönnigmann
我们在工业硬件上实施了最近提出的事件触发网络模型预测控制（MPC）方法，以分析其实际相关性。这种实现存在多种替代方案，它们在本地节点和中央节点之间的计算负载的分布以及网络带宽要求方面有所不同。之前已经对这些替代方案进行了理论上的分析，但是，当实施时，很明显，它们的有用性不能仅根据理论考虑来预测。本简介的目的是在确定哪种替代方案最适合在工业硬件上实施时考虑实践和理论方面。已知最小可能的带宽会产生一种变体，其中仅将活动的约束集从中央节点传输到本地节点。由于在这种情况下，本地节点必须根据活动集确定控制律，这需要矩阵求逆，因此乍一看会产生不具吸引力的计算成本。有点令人惊讶的是，在实施时，计算成本实际上与问题规模成线性比例。我们通过比之前文章中给出的更详细的理论复杂性分析来确认这一结果。所有结果均通过实施工业硬件组件获得的数据进行说明。
We implement a recently proposed event-triggered networked model predictive control (MPC) approach on industrial hardware to analyze its practical relevance. There exist several alternatives for such implementation which differ with respect to the distribution of computational load between local and central nodes and with respect to network bandwidth requirements. These alternatives have been analyzed theoretically before, but, when implemented, it becomes evident that their usefulness cannot be predicted based on theoretical considerations alone. It is the purpose of this brief to account for both practical and theoretical aspects in determining which alternative is most appropriate for implementation on industrial hardware. The smallest possible bandwidth is known to result for a variant in which only the active set of constraints is transmitted from the central to the local nodes. Since local nodes must determine the control law from the active set in this case, which requires matrix inversions, an unattractive computational cost results at first sight. Somewhat surprisingly, the computational cost scales practically linearly in the problem size when implemented. We confirm this result with a more detailed theoretical complexity analysis than given in previous articles. All results are illustrated with data obtained with implementation of industrial hardware components.