基于Lyapunov合成的神经自适应控制器的研制与应用

J. Neidhoefer, C. Cox, R. Saeks
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引用次数: 6

摘要

本文的重点是描述一种基于李亚普诺夫合成技术的神经自适应控制(NAC)技术。NAC是一种非线性自适应控制器,它需要最小的被控对象信息。它可以实时调整其增益,以保持所需的性能,并自动补偿由系统故障、环境变化或组件损坏引起的工厂动态变化。因此,NAC控制技术有可能通过自动优化每个操作状态的控制律来提高系统性能。它还可以通过自动补偿工厂损坏和系统故障来提高可靠性。
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Development and application of a Lyapunov synthesis based neural adaptive controller
The focus of this paper is to describe a neural adaptive control (NAC) technology derived using a Lyapunov synthesis technique. The NAC is a nonlinear adaptive controller which requires minimal plant information. It adapts its gains in real time to maintain the desired performance and to automatically compensate for changes in plant dynamics caused by system failures, environmental changes, or component damage. As such, the NAC control technology has the potential to enhance system performance by automatically optimizing its control laws for each operating regime. It can also increase reliability by automatically compensating for plant damage and system failures.
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