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This paper proposes an adaptive neural network based control scheme for coordinated multiple mobile manipulators in the presence of model uncertainties and external disturbances. A key feature of this scheme is that the prior information of the possible upper bound of the uncertainty is not required. A feedforward neural network (FFNN) is employed to learn this upper bound. The proposed controller not only achieves uniformly ultimate boundedness (UUB) for trajectory tracking error of the object but also keeps the internal force error under a bound. Simulation studies are carried out for coordinated two wheels driven mobile manipulators.

Simulation of Neural Network Based Adaptive Compensator Control Scheme for Multiple Mobile Manipulators with Uncertainties