论文标题
线性随机系统的有限地平线稳健协方差控制的凸优化
Convex optimization for finite horizon robust covariance control of linear stochastic systems
论文作者
论文摘要
这项工作解决了离散时间，可观察到的有限协方差控制问题，该问题受到随机零平均噪声和确定性但未知的干扰的影响，仅在于所谓的Ellitopic不确定性集（例如，在中心椭圆形的/ellips/Elliptics/Elliptic ciliptic ciliptic ciliptic calipters contimenty section sepection consementiantiant os。通过平均凸二次不平等，平均值的线性不平等以及协方差矩阵上指定的上限，对随机状态对照轨迹施加了性能规格。对于这个问题，我们开发了一个可计算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明确凸面程序的解决方案获得的。我们的理论发现通过数值示例说明。
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.
