Convex Optimization for Finite-Horizon Robust Covariance Control of Linear Stochastic Systems
Convex Optimization for Finite-Horizon Robust Covariance Control of Linear Stochastic Systems
复制标题
线性随机系统有限范围鲁棒协方差控制的凸优化
DOI：
10.1137/20m135090x
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发表时间：
2020
期刊：
影响因子：
--
通讯作者：
A. S. Nemirovsky
中科院分区：
文献类型：
--
作者：
Georgios Kotsalis;Guanghui Lan;A. S. Nemirovsky
这项工作解决了离散时间、部分可观测的线性系统的有限范围鲁棒协方差控制问题，该系统受随机零均值噪声和确定性但未知的干扰的影响，这些干扰仅限于所谓的椭圆体不确定集（例如，以原点椭圆体/椭圆柱为中心的有限交集）。通过平均凸二次不等式、均值线性不等式以及协方差矩阵上预先指定的上限，将性能规范强加于随机状态控制轨迹。对于这个问题，我们开发了一种计算上易于处理的程序来设计仿射控制策略，从某种意义上说，保证上述性能规范的策略参数是作为显式凸程序的解决方案获得的。我们的理论发现通过数值例子来说明。
This work addresses the finite-horizon robust covariance control problem for discrete-time, partially observable, linear system affected by random zero mean noise and deterministic but unknown disturbances restricted to lie in what is called ellitopic uncertainty set (e.g., finite intersection of centered at the origin ellipsoids/elliptic cylinders). Performance specifications are imposed on the random state-control trajectory via averaged convex quadratic inequalities, linear inequalities on the mean, as well as pre-specified upper bounds on the covariance matrix. For this problem we develop a computationally tractable procedure for designing affine control policies, in the sense that the parameters of the policy that guarantees the aforementioned performance specifications are obtained as solutions to an explicit convex program. Our theoretical findings are illustrated by a numerical example.
影响因子：
3
作者：
Kazuhide Okamoto;M. Goldshtein;P. Tsiotras
通讯作者：
Kazuhide Okamoto;M. Goldshtein;P. Tsiotras