非线性MIMO系统辨识中的智能混合主动控制

T. Mohamed, K. A. K. Ishak, H. Ramli, M. S. Meon
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引用次数: 1

摘要

提出了一种基于主动控制(AFC)的嵌入神经网络和模糊逻辑的双转子多输入多输出(MIMO)系统设计方案。由于传统PID的局限性,导致难以补偿角动量和两轴间反转向引起的扰动和内部变化,因此提出了这种结构。将该结构应用于俯仰和偏航控制方案中以优化响应。结果表明,所提出的候选算法具有相当好的性能,并且能够补偿内部和外部干扰。神经网络与模糊逻辑的结合是一种很有潜力的混合方法,因为它在加速TRMS性能方面提供了先进的优化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Intelligent hybrid Active Force Control in identification of a nonlinear MIMO system
This paper presents Active Force Control (AFC) based scheme embedded with neural network and fuzzy logic in scheming the twin rotor multi-input multi-output (MIMO) system (TRMS). This architecture is proposed due to limitations of classic PID lead to difficulty in compensate the disturbances and internal changes appertain by angular momentum and reaction turning between two axes. The proposed architecture is employed in both pitch and yaw control scheme to optimize the responses. The results shown a very significant achievement as the proposed candidate give reasonably good performance and capable of compensating the internal and external disturbances. The integration of Neural Network and fuzzy logic is proven to be a potential hybrid as it provides an advanced optimization in accelerates the performance of TRMS.
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