In hard disk drive (HDD) systems, disturbances commonly contain different frequency components that are time-varying in nature. Different HDD systems may subject to different excitation disturbances. In this case, it is difficult for fixed-gain PID controllers to maintain a good overall performance. When the characteristics of the disturbances change, or when servos are designed for different drive products, the PID gains have to be retuned. This paper presents automatic online gain tuning of PID controllers based on neural networks. The proposed control scheme can automatically adjust the PID parameters online in the presence of time-varying disturbances, or for different disturbances among different HDD products, and find the optimal sets of PID gains through the self-learning ability of neural networks.
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ASME 2013 Conference on Information Storage and Processing Systems
June 24–25, 2013
Santa Clara, California, USA
Conference Sponsors:
- Information Storage and Processing Systems Division
ISBN:
978-0-7918-5553-9
PROCEEDINGS PAPER
Neural-Network Based Automatic PID Gain Tuning in the Presence of Time-Varying Disturbances in Hard Disk Drives
Liting Sun,
Liting Sun
University of Science and Technology of China, Hefei, Anhui, China
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Xu Chen,
Xu Chen
University of California at Berkeley, Berkeley, CA
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Masayoshi Tomizuka
Masayoshi Tomizuka
University of California at Berkeley, Berkeley, CA
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Liting Sun
University of Science and Technology of China, Hefei, Anhui, China
Xu Chen
University of California at Berkeley, Berkeley, CA
Masayoshi Tomizuka
University of California at Berkeley, Berkeley, CA
Paper No:
ISPS2013-2948, V001T03A007; 4 pages
Published Online:
December 4, 2013
Citation
Sun, L, Chen, X, & Tomizuka, M. "Neural-Network Based Automatic PID Gain Tuning in the Presence of Time-Varying Disturbances in Hard Disk Drives." Proceedings of the ASME 2013 Conference on Information Storage and Processing Systems. ASME 2013 Conference on Information Storage and Processing Systems. Santa Clara, California, USA. June 24–25, 2013. V001T03A007. ASME. https://doi.org/10.1115/ISPS2013-2948
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