论文标题
带有电子融合系统的神经网络补偿方案的滑动模式控制
Sliding mode control with a neural network compensation scheme for electro-hydraulic systems
论文作者
论文摘要
电湿度伺服系统广泛用于工业应用,例如机器人操纵器,主动悬架,精密机床和航空航天系统。它们比电动机提供了许多优势,包括高力量与重量比,快速响应时间和紧凑的尺寸。然而,由于电源固有的非线性特征,对电湿系统的精确控制无法通过常规线性控制器轻松获得。大多数流量控制阀还可以表现出一些硬性非线性,例如由于阀线轴重叠而导致的死区。这项工作描述了通过未知的死区输入的电湿度系统的神经网络补偿方案的滑动模式控制器的开发。使用Lyapunov稳定性理论证明了闭环信号的界限和收敛性。为了证明控制系统性能,提出了数值结果。
Electro-hydraulic servo-systems are widely employed in industrial applications such as robotic manipulators, active suspensions, precision machine tools and aerospace systems. They provide many advantages over electric motors, including high force to weight ratio, fast response time and compact size. However, precise control of electro-hydraulic systems, due to their inherent nonlinear characteristics, cannot be easily obtained with conventional linear controllers. Most flow control valves can also exhibit some hard nonlinearities such as dead-zone due to valve spool overlap. This work describes the development of a sliding mode controller with a neural network compensation scheme for electro-hydraulic systems subject to an unknown dead-zone input. The boundedness and convergence properties of the closed-loop signals are proven using Lyapunov stability theory. Numerical results are presented in order to demonstrate the control system performance.