Adaptive Neural Control of Nonaffine Nonlinear Systems without Differential Condition for Nonaffine Function

被引:3
作者
Sun, Chaojiao [1 ]
Jing, Bo [1 ]
Liu, Zongcheng [1 ]
机构
[1] Air Force Engn Univ, Coll Aeronaut & Astronaut Engn, Xian 710038, Peoples R China
关键词
NON-AFFINE SYSTEMS; DYNAMIC SURFACE CONTROL; TIME-DELAY SYSTEMS; FUZZY CONTROLLER; TRACKING CONTROL; NETWORK CONTROL; DEAD-ZONE; BACKSTEPPING CONTROL; FEEDBACK CONTROL; BACKLASH;
D O I
10.1155/2016/4085929
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
An adaptive neural control scheme is proposed for nonaffine nonlinear system without using the implicit function theorem or mean value theorem. The differential conditions on nonaffine nonlinear functions are removed. The control-gain function is modeled with the nonaffine function probably being indifferentiable. Furthermore, only a semibounded condition for nonaffine nonlinear function is required in the proposed method, and the basic idea of invariant set theory is then constructively introduced to cope with the difficulty in the control design for nonaffine nonlinear systems. It is rigorously proved that all the closed-loop signals are bounded and the tracking error converges to a small residual set asymptotically. Finally, simulation examples are provided to demonstrate the effectiveness of the designed method.
引用
收藏
页数:11
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