Teleoperation System using Neural Network Based Multiple Model Adaptive Predictive Control

Environment model and communication time delays of teleoperation system are usually variant. These will cause bad performance, even instability of the systems. In this paper, we have developed a theoretical framework to design the neural network based multiple model adaptive predictive controller to solve this problem. First. neural network model base of any possible environment is built up. The teleoperation controller is designed under the effects of time delay. The time forward state observer is built for all environment models to predict slave state. We also established the model of total teleoperation system. Finally, the control parameters can be given conveniently using the result of transparency analysis. The stability, of teleoperation system will be shown by the results of simulation.