一类相似组合大系统的自适应神经网络控制  

Adaptive Neural Network Control for a Class of Nonlinear Composite Systems with Similarity

作　　者：钱荣华[1] 张天平 

机构地区：[1]扬州职业大学,江苏扬州225009 [2]扬州大学,江苏扬州225002

出　　处：《扬州职业大学学报》2009年第3期27-31,共5页Journal of Yangzhou Polytechnic College

摘　　要：针对一类具有未知死区模型和未知增益符号的不确定非线性相似组合大系统,利用简化死区模型,并引入Nussbaum函数,提出一种自适应神经网络滑模控制方法,取消了死区模型参数的上下界必须已知的条件以及控制增益符号已知的假设。通过利用积分型李亚普诺夫函数,证明了闭环系统半全局一致终结有界。The problem of adaptive neural network control for a class of uncertain nonlinear composite systems with unknown dead-zones and an unknown gain sign is discussed in this article. By using the simplified deadzone model and introducing the Nussbaum function, a control method of sliding mode adaptive neural-network is presented, instead of requiring the priori knowledge of the assumption of the control gain and the upper and lower bound of the dead-zone parameter known as priori condition. Based on the theoretical analysis of integral-type function, the closed-loop control system is proven to be semi-globally, uniformly and ultimately bounded.

关 键 词：神经网络控制 滑模控制 自适应控制 NUSSBAUM函数 

分 类 号：O231.2[理学—运筹学与控制论]