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Adaptive neural network control of uncertain nonlinear systems with nonsmooth actuator nonlinearities

机译:具有非光滑执行器非线性的不确定非线性系统的自适应神经网络控制

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摘要

In this paper, we present a new approach of designing adaptive neural network controllers for uncertain systems containing nonsmooth nonlinearities in the actuator device. The controllers are designed by introducing certain well-defined sign functions and neural network approximations as well as by using the backstepping technique. The salient feature of the approach is that no knowledge is assumed on unknown system parameters and nonlinearities. It is shown that the proposed controller not only can guarantee semi-global stability, but also excellent transient performance can be achieved.
机译:在本文中,我们提出了一种为执行器设备中包含非平滑非线性的不确定系统设计自适应神经网络控制器的新方法。通过引入某些定义明确的符号函数和神经网络近似以及使用反推技术来设计控制器。该方法的显着特征是,无需假设未知系统参数和非线性知识。结果表明,所提出的控制器不仅可以保证半全局稳定性,而且可以实现优良的暂态性能。

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