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.
This paper aims to provide a global sliding mode control (GSMC) method using nonlinear extended state observer (NESO) for thermal-structure test (TST). Firstly, the designed control method adopts NESO to observe the internal and external disturbances of the system. Then, the nonlinear global sliding mode surface is constructed to improve control accuracy, speed up convergence and reduce the chattering phenomenon. Finally, the effectiveness and superiority of the proposed method compared with existing control methods are verified by comparison of simulation and experimental results.
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