Robust observer and neurodynamics based distributed formation control of multiple mobile robots

Formation control has been an interesting and ongoing problem in the cooperation of multiple robotic systems. This paper designs a novel bioinspired, observer-based formation control scheme to address challenges, including kinematic constraints, velocity jumps, incomplete state information, robustness against disturbances, and control smoothness under measurement noises. First, a distributed estimator is developed using a cascade design to provide the leader’s estimates without requiring derivative information. Next, a bioinspired state observer is introduced to estimate both unavailable states and disturbances accurately, enabling improved formation performance with smooth state measurements. Then, a neural-dynamic-based kinematic controller is proposed to effectively handle velocity jumps and kinematic constraints. Followed by the kinematic control, a nonlinear dynamic controller is designed to ensure robustness against disturbances. The proposed approach is validated through extensive simulation studies, demonstrating its effectiveness and confirming the theoretical results.