Multiobjective Optimal Control With Safety as a Priority
Multiobjective Optimal Control With Safety as a Priority
复制标题
以安全为优先的多目标最优控制
DOI：
10.1109/tcst.2017.2699161
复制
发表时间：
2018
影响因子：
4.8
通讯作者：
A. Abate
中科院分区：
文献类型：
--
作者：
Kendra Lesser;A. Abate
本文开发了一种词典学方法，用于网络物理系统模型的多目标最优控制，特别是包括随机性，对模型变量的有限访问（部分观测），以及可能的混合（连续和离散）动力学（有限状态部分可观察的马尔可夫决策过程框架作为已知的特殊实例）。该技术在智能建筑领域的两个新案例研究中得到了展示。在技术上，本文的主要成果如下：将词典编纂框架应用于多目标优化，包括定量概率安全要求，从而导致安全的正确设计合成和性能的最佳合成的原则和可扩展集成，将词典编纂框架扩展到具有连续（可能混合）动态的部分观察随机模型，并强调计算方面。包括使用价值函数的紧凑和近似表示，并结合模型抽象的误差界限的量化。
This paper develops a lexicographic approach to multiobjective optimal control on models for cyber-physical systems, encompassing in particular stochasticity, limited access to model variables (partial observations), and possibly hybrid (continuous and discrete) dynamics (with the finite-state partially observable Markov decision process framework as a known special instance). The technique is showcased in two new case studies in the area of smart buildings. Technically, the main achievements of this paper are as follows: the application of the lexicographic framework to multiobjective optimization including quantitative probabilistic safety requirements, thus leading to a principled and scalable integration of correct-by-design synthesis for safety and optimal synthesis for performance, the novel extension of the lexicographic framework to partially observed stochastic models with continuous (possibly hybrid) dynamics, and the emphasis on computational aspects, including the use of compact and approximate representations of value functions combined with the quantification of error bounds on model abstractions.