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.

翻译：本条为有偏差测量的网络化双集成系统达成共识制定了新的分布式控制法; 代理人用一个时间变化的、无方向分布式的图表测量相对位置,其传感器偏差不明且始终存在,从而腐蚀测量结果; 利用Lyapunov方法得出适应性控制法,以准确估计单个传感器偏差; 拟议的算法确保除了偏见估计之外还成指数地取得定位共识; 其结果利用了适应性估计方面集体初步引力结果的最新进展; 也开发了将双面图和集体初步引力联系起来的条件; 通过模拟研究用当地通信和偏差测量的双重集成者网络来说明算法。