论文标题
基于数据的线性网络系统的后退视野控制
Data-based Receding Horizon Control of Linear Network Systems
论文作者
论文摘要
我们提出了一种基于数据的预测控制方案，以稳定线性动力学描述的网络系统。代理商合作以预测未来的系统演变，而无需了解动态，而是依靠从单个样本轨迹学习基于数据的表示。我们采用这种表示形式来重新将有限的线性二次调节剂问题作为具有可分离的目标函数和本地表达约束的网络优化。我们表明，使用分布式优化算法以退缩的方式稳定了使用分布式优化算法而产生的控制器，这是稳定的。我们通过数值模拟来验证结果。
We propose a distributed data-based predictive control scheme to stabilize a network system described by linear dynamics. Agents cooperate to predict the future system evolution without knowledge of the dynamics, relying instead on learning a data-based representation from a single sample trajectory. We employ this representation to reformulate the finite-horizon Linear Quadratic Regulator problem as a network optimization with separable objective functions and locally expressible constraints. We show that the controller resulting from approximately solving this problem using a distributed optimization algorithm in a receding horizon manner is stabilizing. We validate our results through numerical simulations.
