Design of fractional-order global sliding mode controller for thermal-structure test based on neural network

In this paper, a Fractional-Order Global Sliding Mode Control (FOGSMC) scheme based on a neural network with approximation property (NNO) is mainly focused on study the Thermal-Structural Test (TST) system. Since the nonlinear dynamic system of the thermal-structure test with quartz lamp is susceptible to external interference and parameter variation, a novel FOGSMC system is designed based on improved fractional order global terminal sliding surface to acquire the desired trajectory, and real time estimation of system disturbance using neural network observer with Gaussian Function, meanwhile, the fractional-order global terminal sliding mode surface based on fractional-order function can effectively weaken the chattering phenomenon of the integer order, simulation studies show the effectiveness of the proposed method.