模糊/神经自适应控制及其在非线性系统中的应用  

Adaptive Fuzzy/Neural Control and its Applications in Nonlinear Systems

作　　者：吴九天[1] 李冬辉[1] 贾巍[1] 

机构地区：[1]天津大学电气与自动化工程学院,天津300072

出　　处：《计算技术与自动化》2005年第4期9-12,共4页Computing Technology and Automation

摘　　要：针对连续未知非线性系统,提出一种基于观测器并保证稳定性和有界性的自适应模糊/神经算法。本算法利用T-S模糊系统或者神经网络径向基函数构成间接自适应控制器,其参数根据控制率和自适应率进行在线调整,并利用Lyapunov综合法确保对非线性环节渐进跟踪的稳定性。最后,通过对倒立摆系统的仿真,证明该算法在非线性系统控制中应用的可行性。In this paper, for a class of unknown continual nonlinear systems, an observer- based adaptive fuzzy/neural control algorithm which can atisfy the stability and boundedness of the systems is developed. The algorithm makes use of T- S （Takagi - Sugeno） fuzzy systems or radial - basis functions to construct the indirect adaptive controller, whose parameters can be adjusted on line according to the control law and the adaptive law in order to provide asymptotic tracking of a reference signal of the nonlinear plants. The Lyapunov- synthesis approach is utilized to insure the stability of the system. Simulation results of the inverted pendulum system are represented to show the feasibility of the algorithm in controlling nonlinear systems.

关 键 词：间接自适应控制 模糊控制 非线性系统 倒立摆 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]