Distributed adaptive impedance control of networked Lagrangian systems with neighborhood interaction feedback

In this study, a new distributed impedance control is proposed in networked Lagrangian systems to improve the compliant performance of each node in respective environment. Different from previous state consensus, this control objective focuses on the dynamic impedance cooperation of networked Lagrangian systems. The augmented impedance error is introduced in the distributed impedance control frame to evaluate the compliant performance of the designed controller. Based on this impedance control frame, the virtual interaction field is proposed to address some typical tasks such that avoid node collision and ensure high cooperation of neighborhood nodes. Then a distributed adaptive impedance controller together with the radial basis function neural network is employed to compensate the model uncertainties of networked Lagrangian systems and guarantee each note convergence to the prescribed dynamic impedance model, which is governed by the robot-environment interaction. Finally, the comparative simulations have verified the effectiveness of the proposed distributed impedance control method.