论文标题
考虑州不可预测性的移动代理的多周期最佳控制
Multi-period Optimal Control for Mobile Agents Considering State Unpredictability
论文作者
论文摘要
移动代理的最佳控制是一个重要且具有挑战性的问题。最近的工作表明，在代理人的控制中使用随机机制可以使状态无法预测，从而提高了代理的安全性。但是，仅在单个时期内考虑不可预测的设计，这可能会导致长期无法忍受的控制性能。本文的目的是在长期范围内的控制绩效与状态不可预测性之间的不可预测性之间进行权衡。利用与统一分布一致的随机扰动来最大化攻击者对未来状态的预测错误，我们将问题作为多期凸的随机优化问题提出问题，并通过动态编程来解决它。具体而言，我们设计了未约束和输入约束系统的最佳控制策略。进一步提供了对照的分析迭代表达。模拟说明该算法在成功达到控制绩效要求的同时增加了Kalman过滤器下的预测错误。
The optimal control for mobile agents is an important and challenging issue. Recent work shows that using randomized mechanism in agents' control can make the state unpredictable, and thus improve the security of agents. However, the unpredictable design is only considered in single period, which can lead to intolerable control performance in long time horizon. This paper aims at the trade-off between the control performance and state unpredictability of mobile agents in long time horizon. Utilizing random perturbations consistent with uniform distributions to maximize the attackers' prediction errors of future states, we formulate the problem as a multi-period convex stochastic optimization problem and solve it through dynamic programming. Specifically, we design the optimal control strategy considering both unconstrained and input constrained systems. The analytical iterative expressions of the control are further provided. Simulation illustrates that the algorithm increases the prediction errors under Kalman filter while achieving the control performance requirements successfully.
