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Adaptive neural network control for pure-feedback nonlinear time delay systems with triangular control structure

机译:具有三角控制结构的纯反馈非线性时滞系统的自适应神经网络控制

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In this paper, adaptive neural network control is investigated for a class of nonlinear systems under the effects of time delay and uncertain nonlinear functions. The system is described in form of pure-feedback and triangle structure, and the virtual control law is proposed to solve the mismatch problem. The unknown functions are approximated by adaptive neural networks and the weights of the neural network are iteratively and adaptively updated through the system state. To overcome the controller singular problem, integral-type Lyapunov function is utilized, the closed-loop control system is proved to be semiglobally uniformly ultimately bounded (SGUUB). A number of bench mark tests are simulated to demonstrate the effectiveness of the proposed approach.
机译:本文研究了一类非线性系统在时滞和不确定非线性函数作用下的自适应神经网络控制。该系统以纯反馈和三角结构的形式描述,并提出了虚拟控制律来解决不匹配问题。未知函数通过自适应神经网络进行近似,并且神经网络的权重通过系统状态进行迭代和自适应更新。为了克服控制器奇异的问题,利用积分型Lyapunov函数,证明了该闭环控制系统是半全局一致的最终有界的(SGUUB)。模拟了许多基准测试,以证明所提出方法的有效性。

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