A Sliding Mode Reaching Law Based on Hermit Neural Network

One of the most popular methods in nonlinear control systems is sliding mode control. Despite its simplicity, speed and robustness, there is a high frequency dynamics caused by delay switching of control law, which is called chattering. So, to treat the chattering problem, a Sliding Mode Reaching Law based on the Recurrent Hermit Neural Network is proposed. The proposed law appears an ability to dampen the chattering, achieve faster reaching to the sliding surface and reduce the impact of tracking errors on system performance. Finally, the proposed method was modeled and tested using MATLAB software.