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Observer-based synergetic adaptive neural network control for a class of discrete-time nonlinear systems with dead-zone

机译:基于观察者的协同自适应神经网络控制,用于死区的一类离散时间非线性系统

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摘要

In this paper, the observer-based synergetic adaptive neural network control method is designed for a class of discrete-time systems with dead-zone. A macro-variable is introduced by a synergetic approach to control theory and neural networks are utilised to estimate unmeasured states and unknown functions in the system. Furthermore, by employing an adaptive design procedure and Lyapunov stability theory, the closed-loop system stability is guaranteed, and the desired system performance is achieved simultaneously. Finally, some simulation results are given to prove the validity of the developed control method.
机译:在本文中,设计了基于观察者的协同自适应神经网络控制方法,用于一类具有死区的离散时间系统。通过协同方法引入宏变量来控制理论,并且神经网络用于估计系统中的未测量状态和未知功能。此外,通过采用自适应设计程序和Lyapunov稳定性理论,保证闭环系统稳定性,同时实现所需的系统性能。最后,给出了一些模拟结果来证明开发控制方法的有效性。

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