Adaptive intelligent terminal sliding mode controller for stabilizing a chaotic plasma torch system

In this article, a novel adaptive intelligent control scheme is proposed to stabilize a chaotic nonlinear system with unknown dynamics in the presence of uncertainties and external disturbances. The proposed control scheme is a combination of terminal sliding mode, adaptive, and neural controllers. Terminal sliding mode control provides appropriate finite-time stability and robustness against uncertainties and external disturbances. A neural controller is used to provide suitable control action to eliminate chattering when the sliding surface is close to zero. For this purpose, a fuzzy module with simple rules is used to change the contributions of two neural and terminal sliding mode controllers, that is, when the sliding surface has a value around zero, the neural controller will take the control of the system to reduce chattering, and when the sliding surface is far from the zero region, the terminal sliding mode controller will control the system. Moreover, to cope with the unknown dynamics of the system, an online adaptive neural network is also used to approximate the unknown dynamics of the system. This hybrid control scheme is capable to decrease the contribution of the terminal sliding mode in the convergence region of the sliding surface which leads to the elimination of chattering. The combination of the several techniques to use the advantages of all the methods makes the proposed hybrid control scheme as an effective and practical scheme. Simulation results on a chaotic plasma torch system indicate the efficiency of the proposed control scheme in chattering elimination, high convergence, and also show the superior performance compared with the existing methods in the presence of disturbance and uncertainty.