Adaptive backstepping asymptotic consensus tracking control of multiple uncertain manipulators with disturbances

Abstract

Abstract This article studies the asymptotic consensus of multiple robots with uncertain parameters and external disturbances. A novel asymptotic tracking command filtered adaptive consensus control approach is proposed. The command filters avoid the differentials of virtual control functions in backstepping, meanwhile, the compensation mechanism is used to compensate filtering errors. Compared with current command filtered control algorithms for the consensus control of multiple robots, the consensus tracking errors can asymptotically converge to origin under the given approach, moreover, the design process is simplified by designing only one adaptive parameter for each manipulator. A simulation example verifies the given approach.