Distributed convex optimization of time-varying cost functions for double-integrator systems using nonsmooth algorithms
Distributed convex optimization of time-varying cost functions for double-integrator systems using nonsmooth algorithms
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DOI：
10.1109/acc.2015.7170713
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发表时间：
2015-07
期刊：
影响因子：
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通讯作者：
Salar Rahili;W. Ren;Peng Lin
中科院分区：
文献类型：
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作者：
Salar Rahili;W. Ren;Peng Lin
在本文中，推导了非滑动算法来解决具有双重整合器动力学的连续时间多代理系统的时变分布式凸优化问题。目的是最大程度地减少局部时间变化的成本函数的总和，每个函数仅通过局部互动才能为单个代理所知道。这里的最佳点是时间变化。首先，引入了一种集中式方法来解决单一集成剂动力学的强烈符合时间变化功能的优化问题。其次，该问题以分布式方式解决了具有双整合器动力学的多机构系统。提出了一种非滑动算法，每个代理仅依赖于其自身的位置以及自身与其邻居之间的相对位置和速度。因此，如果代理配备了传感功能，则无需通信。权衡是，对可行的成本功能实施了更加限制的假设。第三，提出了一种估算器跟踪的非滑动算法，其中每个代理使用从其邻居传达的信息生成内部信号。然后，每个代理通过跟踪此内部信号来最大程度地减少团队成本功能。在这里，对可行成本功能的假设放宽了。
In this paper, nonsmooth algorithms are derived to solve a time-varying distributed convex optimization problem for continuous-time multi-agent systems with double-integrator dynamics. The objective is to minimize the sum of local time-varying cost functions, each of which is only known to an individual agent through local interactions. Here the optimal point is time varying. First, a centralized approach is introduced to solve the optimization problem with strongly-convex time-varying functions for single-integrator dynamics. Second, the problem is solved in a distributed manner for multi-agent systems with double-integrator dynamics. A nonsmooth algorithm is proposed where each agent relies only on its own position and the relative positions and velocities between itself and its neighbors. Hence communication is not necessary if the agents are equipped with sensing capabilities. The trade off is that a more restricted assumption is imposed on feasible cost functions. Third, an estimator-tracking nonsmooth algorithm is proposed where each agent generates an internal signal using information communicated from its neighbors. Then each agent minimizes the team cost function by tracking this internal signal. Here the assumption on feasible cost functions is relaxed.