Inverse Model-Based Iterative Learning Control for Active Control of Repetitive Impulsive Noise with a Non-minimum Phase Secondary Path

摘要：

In this paper, active control of impulsive noise is studied. A novel approximate inverse model combined with optimal criterion-based iterative learning control (ILC) algorithm is used for an active noise control (ANC) system with a non-minimum phase secondary path. Computer simulations have been carried out to validate the effectiveness of the proposed algorithm. The plant model used in the computer simulations is obtained from a practical ANC system in our laboratory. Simulation results show that the proposed scheme can significantly reduce the impulsive noise and the convergence rate is fast for a non-minimum phase plant.

关键词： Active noise control Repetitive impulsive noise Non-minimum phase Iterative learning control Inverse model

作者: ZHOU Yali YIN Yixin ZHANG Qizhi

作者单位: School of Automation, University of Science and Technology Beijing, Beijing 100083 School of Automat School of Automation, University of Science and Technology Beijing, Beijing 100083 School of Automation, Beijing Information Science and Technology University, Beijing 100192, China

会议类型: 国际会议

会议名称: The 31st Chinese Control Conference(第三十一届中国控制会议)

会议地点: 合肥

会议语种:英文

页码: 2917-2921

在线出版日期: 2012-07-01（万方平台首次上网日期，不代表论文的发表时间）