Synchronization Control And Experimental Validate For Networked Teleoperation System

The robotic teleoperation system is a comprehensive subject which includes robotics, network communications, control theory and so on. Teleoperation is a challenging topic with a number of applications, such as telesurgery, space and undersea exploration, and radiation detection. The research of domestic teleoperation system have started relatively later than it in the developed countries and is not very mature. Teleoperation system deserves enormous potential and space for development based on the periodical achievement. Especially some unavoidable actual problems exist in the system, for example, system uncertainties, external disturbances, states constrains, input constrains and time delay, which increased the research difficulties. This paper aims at researching the synchronization problem based on the system which contains uncertainties, external disturbances, transmission delay, and achieves the finite-time synchronization. Asymptotic stability is realized under the condition that input constrains. The simulations and experiments results validate the effectiveness of the proposed control strategy. The main works of this paper can be summarized as follow.Firstly, according to the Eulerian-Lagrangian system mode, the dynamics properties and some related mathematical properties are illustrated. Additionally, the basic concepts of extended-state-observer(ESO) and finite-time control are introduced, which provide the theoretical basis for the application of the control algorithm.Secondly, the position synchronization problem is researched. In the process of the controller design, apply the ESO to deal with the internal uncertainties and external disturbance in the master and slave side. Lyapunov function is designed to analysis the system stabilities and synchronization performance, and the finite-time control is achieved. Compared with the traditional P+d controller, the effectiveness of the proposed control strategy is more efficient through the experiments on the phantom.Finally, the auxiliary control system is introduced to deal with the input saturation. Neural network is used to handle the uncertainties and the external disturbance, and the asymptotic stability is achieved. The simulations validate the effectiveness of the control strategy.