Tracking Control of Neural System using Adaptive Sliding Mode Control for Unknown Nonlinear Function

In this article, a sliding mode control (SMC) is used to design the tracking control for the neural system based on a networked control system (NCS) that appeared with time delays. First, we established the mathematical forms for the stability analysis, and then proposed the radial basis function to approximate the nonlinear function. Second, we propose the discrete event-triggered scheme (ETS) as a way to make better use of existing bandwidth. Only when our sampled data of plant violates the specific event-triggered condition does the sensor release the data under this ETS. Finally, a nonlinear example is given to demonstrate the effectiveness of our co-design method.