非仿射系统的自学习滑模抗扰控制
Self-learning sliding-mode disturbance rejection control for non-affine systems

针对一类单输入单输出(single-input single-output, SISO)非仿射非线性系统的控制问题, 提出了一种自学习 滑模抗扰控制方法. 该方法用非线性光滑函数设计扩张状态观测器, 实现SISO 非仿射非线性系统内部不确定性和 外部扰动的扩张状态估计, 并将扩张状态观测器(extended state observer, ESO)与自学习滑模控制技术融为一体, 实 现SISO非仿射非线性系统的自学习滑模抗扰控制. 该方法不依赖受控对象的数学模型, 可以快速跟踪任意给定的 参考信号. 数值仿真试验表明了该方法响应速度快、控制精度高, 具有很强的抗扰动能力, 因而是一种鲁棒稳定性很 强的控制方法, 在SISO非仿射非线性系统控制领域具有重要作用.
Disturbance rejection control (DRC) method with self-learning sliding mode (SLSM) is proposed for a class of single-input single-output (SISO) non-affine nonlinear systems (NANS). The proposed method realizes the extended state estimation of internal parameters perturbation and external disturbances of the NANS based on extended state observer (ESO) designed by nonlinear smooth function. Sliding mode disturbance rejection control (SMDRC) for SISO NANS with uncertainties and disturbance is realized by the technology based on the ESO combined with auto-learning sliding mode control (ALSMC). The method is not dependent on the mathematical model of the controlled plants, and can fast track any given reference signal. Numerical simulation results show that the proposed method not only has fast response, high control precision, but also has strong disturbance-rejection ability for the non-affine nonlinear systems with internal and external disturbance. So the proposed control method will play an important role in control field of the SISO NANS because of its strong robust stability.