Distributed Adaptive Formation Control for Nonholonomic Mobile Robots over Noisy Communication Networks

In this paper, we solve the formation problem of nonholonomic mobile robots (NMRs) over noisy communication networks. The communication signals with noisy information are exchanged among different NMRs by a directed graph. Only the individual mobile robot directly receives the actual and feasible signals itself without communication. Besides, the sensor-to-control signals suffering from the noise are modeled by a nonlinear function including unknown parameters and uncertainties. Combined with the adaptive control technique and robust control technique, the unknown parameters and uncertainties of noisy signal models are respectively estimated and compensated, respectively. Then, a novel distributed adaptive formation controller is proposed to guarantee convergence to the optimal positions over noisy communication networks. It is proved that the formation errors are convergent to a small neighbourhood of origin and closed-loop signals of each NMRs are bounded. A simulation example is given to demonstrate the theoretical studies.