A new neural network structure dedicated to the control of nonlinear systems

Tsurng-Jehng Shen, F. Mora-Camino, K. Achaibou
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Abstract

Proposes a new neural network structure to design a robust controller for non-exactly known nonlinear systems. Based on input-output data, the neural network structure provides a global affine model of the controlled system which is compatible with well known nonlinear control techniques. An affine neural tracking controller is developed and applied to an inverted pendulum submitted to random perturbations. The performance of the controller and the main advantage of the proposed approach are discussed.
一种用于非线性系统控制的新型神经网络结构
提出了一种新的神经网络结构来设计非完全已知非线性系统的鲁棒控制器。基于输入输出数据,神经网络结构提供了被控系统的全局仿射模型,该模型与已知的非线性控制技术兼容。提出了一种仿射神经跟踪控制器,并将其应用于受随机扰动的倒立摆。讨论了控制器的性能和所提方法的主要优点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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