An adaptive neural sliding mode control with ESO for uncertain nonlinear systems is proposed to improve the stability of the control system. Any control system inevitably exists uncertain disturbances and nonlinearities which severely affect the control performance and stability. Neural network can be utilized to approximate the uncertain nonlinearities. Nevertheless, it produces approximate errors, which will become more difficult to deal with as the order of the system increases. Moreover, these errors and uncertain disturbances will result in a consequence that the control system can be unable to converge quickly, and has to deal with a lot of calculations. Therefore, in order to perfect the performance and stability of the control system, this paper combines sliding mode control and ESO, and designs an adaptive neural control method. The simulation results illustrate that the improved system has superior tracking performance and anti-interference ability.
Abstract— The electron source is an essential part of a surface‐conduction electron‐emitter display (SED). An electron source for an SED was obtained after certain procedures were performed. By introducing a carbon atmosphere, the electron‐emission characteristics of a SED were studied experimentally. The electron‐emission characteristic curves were drawn after comparing the experimental data of the electron source obtained in a vacuum environment with the data obtained in a carbon atmosphere, from which it had proved that a carbon atmosphere could significantly improve the electron‐emission characteristics of a SED. As a result, both the device current and the emission current had become stronger and the efficiency of surface‐conduction electron emission had been improved significantly. The possible reasons were analyzed: more carbon, which could possibly form the electron‐emission region of a SED, was produced from the carbon atmosphere during the electrical activation process. 相似文献