引用本文:刘　亚, 侯　霞, 胡寿松.基于自适应AGBFN的不确定非线性系统的跟踪控制[J].控制理论与应用,2005,22(1):29~34.[点击复制]
LIU Ya, HOU Xia, HU Shou-song.Tracking control for uncertain nonlinear system based on adaptive asymmetric Gaussian basis function network[J].Control Theory and Technology,2005,22(1):29~34.[点击复制]
基于自适应AGBFN的不确定非线性系统的跟踪控制
Tracking control for uncertain nonlinear system based on adaptive asymmetric Gaussian basis function network
摘要点击 1613  全文点击 1093  投稿时间：2003-07-01  修订日期：2004-01-14
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DOI编号  10.7641/j.issn.1000-8152.2005.1.006
  2005,22(1):29-34
中文关键词  不对称高斯基函数  自适应神经网络  跟踪控制  不确定非线性系统
英文关键词  asymmetric Gaussian basis function(AGBF)  adaptive neural network  tracking control  uncertain nonlinear system
基金项目  国家自然科学基金重点资助项目(60234010).
作者单位
刘　亚, 侯　霞, 胡寿松 南京航空航天大学 自动化学院,江苏 南京 210016 
中文摘要
      针对一类具有未知不确定性的非线性系统,提出了一种基于观测器的自适应不对称高斯基函数网络(AGBFN)跟踪控制方案.当系统只有输出可以测量时,通过设计观测器对其进行在线状态估计,进而构造反馈控制律和自适应控制律.所提出的完全自适应AGBFN,可以在线更新网络所有参数,克服了传统RBF网络对称性约束,提高了网络的适应性和学习能力,可以有效地对消系统未知不确定项的影响.证明了闭环系统所有误差信号最终一致有界,且系统输出较好地跟踪参考模型输出.仿真结果表明了所提出方法的有效性.
英文摘要
      An observer-based adaptive asymmetric Gaussian basis function network (AGBFN) tracking control scheme is designed for a class of nonlinear system with unknown uncertain nonlinearities.When only the output of the system is measurable,the observer is designed for state estimation,and then feedback control law and adaptive control law are developed.The proposed full adaptive AGBFN,which eliminates the symmetry restriction of traditional RBFN and provides the neurons with higher flexibility,can get rid of the effect of the unknown uncertainties by updating all parameters of the AGBFN online.All the errors in closed-loop nonlinear system are uniformly ultimately bounded and the output of the system is proven to converge to a small neighborhood of the desired trajectory.Simulation shows that the proposed method is effective.