Optimal Safe Controller Synthesis: A Density Function Approach

Optimal Safe Controller Synthesis: A Density Function Approach
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最优安全控制器综合:密度函数方法

DOI:
10.23919/acc45564.2020.9147721
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发表时间:
2019
期刊:
2020 American Control Conference (ACC)
影响因子:
--
通讯作者:
A. Ames
A. Ames
中科院分区:
--
文献类型:
--
作者:
Yuxiao Chen;M. Ahmadi;A. Ames

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本文考虑基于密度函数的最优安全控制器的综合问题。利用密度函数和值函数之间的对偶关系,提出了一种鲁棒约束最优控制综合算法。密度函数遵循刘维方程,并且是值函数的对偶,满足贝尔曼最优性原理。由于密度函数,状态分布的约束,如安全约束,可以直接在最优控制问题中提出。约束最优控制问题,然后解决了原始-对偶算法。这种提法是扩展到外部干扰的情况下,我们表明,鲁棒约束最优控制可以解决一个修改的原始-对偶算法。我们将此配方的问题,找到最佳的安全控制器,最大限度地减少累积干预。一个自适应巡航控制(ACC)的例子被用来证明所提出的有效性,其中我们比较的结果与传统的控制障碍函数(CBF)的方法的密度函数的方法。
This paper considers the synthesis of optimal safe controllers based on density functions. We present an algorithm for robust constrained optimal control synthesis using the duality relationship between the density function and the value function. The density function follows the Liouville equation and is the dual of the value function, which satisfies Bellman’s optimality principle. Thanks to density functions, constraints over the distribution of states, such as safety constraints, can be posed straightforwardly in an optimal control problem. The constrained optimal control problem is then solved with a primal-dual algorithm. This formulation is extended to the case with external disturbances, and we show that the robust constrained optimal control can be solved with a modified primal-dual algorithm. We apply this formulation to the problem of finding the optimal safe controller that minimizes the cumulative intervention. An adaptive cruise control (ACC) example is used to demonstrate the efficacy of the proposed, wherein we compare the result of the density function approach with the conventional control barrier function (CBF) method.
通过凸松弛的多项式混合系统的最优控制
DOI: 10.1109/tac.2019.2929110
发表时间: 2020
影响因子: 6.8
作者:
Zhao, Pengcheng;Mohan, Shankar;Vasudevan, Ram
通讯作者: Vasudevan, Ram
DOI: 10.1109/lcsys.2017.2710943
发表时间: 2017-10-01
影响因子: 3
作者:
Glotfelter, Paul;Cortes, Jorge;Egerstedt, Magnus
通讯作者: Egerstedt, Magnus