Application of infinite mode networks theory to haptic teleoperation for noise suppression

In this paper, a novel multi input multi output network model entitled as "infinite mode networks" is explained. The model proposes a new and challenging design concept. It has mathematically clear input output relationship compared to neural networks. This new model has a desired embedded internal function which roughly determines a route for the whole system to follow as DNA does for biological systems. By this model, infinitely many error dimensions can be defined and each error converges to zero in a stable manner. Additional to the network theory, applications on a four channel haptic bilateral teleoperation control system whose performance is degraded via feedback and feedforward sensor noise are shown. This type of noise suppression is challenging because of two reasons: to obtain an ideal performance disturbance observers necessitate high gains that in turn make the system unstable under feedback and feedforward noises, in a four channel structure noise is reflected back and forth to both bilateral robots which in turn results in unpurified force and position data.