论文标题
部分可观测时空混沌系统的无模型预测
Consensus of networked double integrator systems under sensor bias
论文作者
论文摘要
本文开发了一种具有偏置测量的网络双积分系统共识的新型分布式控制法。代理测量相对位置在随着时间变化的，无方向的图表上，具有未知和恒定的传感器偏置损坏测量结果。使用Lyapunov方法得出自适应控制定律，以准确估计单个传感器偏见。所提出的算法确保除了偏置估计外，达成指数达成共识。结果利用了基于集体初始激发的最新进展，基于自适应估计。还开发了连接两分图和集体初始激发的条件。通过对具有局部通信和偏见测量的双集成商网络的仿真研究来说明算法。
A novel distributed control law for consensus of networked double integrator systems with biased measurements is developed in this article. The agents measure relative positions over a time-varying, undirected graph with an unknown and constant sensor bias corrupting the measurements. An adaptive control law is derived using Lyapunov methods to estimate the individual sensor biases accurately. The proposed algorithm ensures that position consensus is achieved exponentially in addition to bias estimation. The results leverage recent advances in collective initial excitation based results in adaptive estimation. Conditions connecting bipartite graphs and collective initial excitation are also developed. The algorithms are illustrated via simulation studies on a network of double integrators with local communication and biased measurements.
