控制理论(社会学)
噪音(视频)
自回归模型
控制器(灌溉)
主动噪声控制
振动
路径(计算)
信号(编程语言)
计算机科学
窄带
算法
数学
降噪
控制(管理)
统计
人工智能
图像(数学)
物理
生物
程序设计语言
电信
量子力学
农学
作者
Paulo A. C. Lopes,José A. B. Gerald
标识
DOI:10.1016/j.ejcon.2023.100905
摘要
Feedback active noise and vibration control (ANVC) reduces narrowband noise and vibration when there is no reference signal. However, most ANVC algorithms require a secondary path (plant) model and can become unstable when this model is inaccurate. This work proposes an algorithm less sensitive to plant modeling errors and can cope with large and fast plant changes. This is achieved by modeling the plant and the noise using an autoregressive exogenous input (ARX) model. This model allows obtaining the expected values of the future residual noise and determining the optimal control signal. Since the model coefficient uncertainty (variance) is considered when calculating the expected value, the resulting controller is a careful controller. This allows solving problems due to significant model estimation errors when information is insufficient to estimate the full ARX model.
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