sliding mode control

This paper explores the finite-time synchronization problem of delayed complex valued neural networks with time invariant uncertainty through improved integral sliding mode control.  Firstly, the master-slave complex valued neural networks are transformed into two real valued neural networks through the method of separating the complex valued neural networks into real and imaginary parts.  Also, the interval uncertainty terms of delayed complex valued neural networks are converted into the real uncertainty terms.  Secondly, a new integral sliding mode surface is designed by employing the ma

Today, several methods are proposed and tested for controlling many nonlinear and unstable systems. This study employed the sliding mode control (SMC) and proportional-derivative (PD), which are used to control the position and modeling of ball and beam system that is a fundamental system used to test the control methods. Such systems are nonlinear and unstable due to their nature. Therefore, these systems are affected by external disturbances and this leads to a decrease in the control quality.