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首页> 外文期刊>International Journal of Innovative Computing Information and Control >ADAPTIVE NEURAL CONTROL DESIGN FOR A CLASS OF PERTURBED NONLINEAR TIME-VARYING DELAY SYSTEMS
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ADAPTIVE NEURAL CONTROL DESIGN FOR A CLASS OF PERTURBED NONLINEAR TIME-VARYING DELAY SYSTEMS

机译:一类摄动非线性时变时滞系统的自适应神经控制设计

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摘要

In this thesis, Some adaptive neural control design ways are presented for a class of multi-input multi-output (MIMO) nonlinear systems in block-triangular form with disturbance input and state time-varying delay. Neural networks are employed to approximate the unknown continuous functions. By combining the use of a novel quadratic-type Lyapunov-Krasovskii functionals and adaptive NN backstepping, an adaptive neural controller is obtained, which efficiently avoids the controller singularity. The proposed control guarantees that all closed-loop signals remain bounded, while the output tracking error dynamics converges to a neighborhood of the desired trajectories. The feasibility is investigated by a simulation example.
机译:本文针对具有干扰输入和状态时变时滞的块三角形式的一类多输入多输出(MIMO)非线性系统,提出了一些自适应神经控制的设计方法。使用神经网络来近似未知的连续函数。通过结合使用新颖的二次型Lyapunov-Krasovskii函数和自适应NN反推,获得了自适应神经控制器,该控制器有效地避免了控制器的奇异性。所提出的控制保证了所有闭环信号都保持有界,而输出跟踪误差动态收敛于所需轨迹的附近。通过仿真实例研究了可行性。

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