Nonlinear robust adaptive object manipulation by coordinated robotic arms employing Bleimann, Butzer, and Hahn operators for uncertainty estimation

摘要

Abstract Function approximation techniques (FAT) are a potent mathematical tool recently applied to create controllers for handling objects with multiple manipulators without relying on a specific model. However, its effectiveness is contingent on having velocity measurements, which might not be accessible in numerous real‐world scenarios. This paper addresses the issue by introducing a robust adaptive controller using Bleimann, Butzer, and Hahn operators as uncertainty approximators without velocity measurements. Utilizing the Lyapunov lemma, the error signals in the controlled system are guaranteed to remain Uniformly Ultimately Bounded (UUB). The proposed controller will eventually be implemented in a cooperative system where two arms handle a rigid object. The efficiency and effectiveness of the proposed approach are demonstrated through simulation results.