Collaborative Learning Tracking for Networked Systems with Fading Communication

Using a networked structure, many subsystems can communicate and collaborate to accomplish a global objective. With collaborative learning control, the system enables high-precision tracking of repetitive tasks. However, the transmitted signal generally suffers damage in the network. The fading problem is one of the concerns being addressed. To this end, this article investigates collaborative learning control systems in fading channels. We propose a control algorithm equipped with decreasing learning gain. Then, we prove that the reference trajectory can be accurately realized in mean square sense. Finally, we provide numerical simulations to verify our method.