Repeatable Runout Following in Bit Patterned Media Recording

2014 ◽  
Author(s):  
Behrooz Shahsavari ◽  
Ehsan Keikha ◽  
Fu Zhang ◽  
Roberto Horowitz
Keyword(s):  
Controller Design ◽  
Hard Disk Drives ◽  
Lms Algorithm ◽  
Variable Step Size ◽  
Step Size ◽  
Bit Patterned Media ◽  
Patterned Media ◽  
Periodic Input ◽  
Feedforward Controller ◽  
Adaptive Feedforward

An adaptive feedforward controller design for tracking repeatable runout (RRO) in bit patterned media recording (BMPR) is proposed for single stage hard disk drives (HDD). The technique is based on a modified filtered-x least mean squares (MFX-LMS) algorithm with deterministic periodic input, and a novel variable step size that boosts both the convergence rate and the steady state error. Comprehensive simulations are provided to show the effectiveness of the proposed method.

Adaptive Repetitive Control Using a Modified Filtered-X LMS Algorithm

2014 ◽  
Author(s):  
Behrooz Shahsavari ◽  
Ehsan Keikha ◽  
Fu Zhang ◽  
Roberto Horowitz
Keyword(s):  
Reference Signal ◽  
Hard Disk Drives ◽  
Hard Disk ◽  
Disk Drive ◽  
Adaptive Controller ◽  
Lms Algorithm ◽  
Path Modeling ◽  
Step Size ◽  
Bit Patterned Media ◽  
Periodic Disturbances

In this paper we employ a modified filtered-x least mean squares (MFX-LMS) method to synthesis an adaptive repetitive controller for rejecting periodic disturbances at selective frequencies. We show how a MFX-LMS algorithm can be utilized when the reference signal is deterministic and periodic. A new adaptive step size is proposed with the motivation to improve the convergence rate of the MFX-LMS algorithm and fade the steady state excess error caused by the variation of estimated parameters in a stochastic environment. A novel secondary path modeling scheme is proposed to compensate for the modeling mismatches online. We further discuss the application of this adaptive controller in hard disk drives that use Bit Patterned Media Recording. Finally we present the results of comprehensive realistic numerical simulations and experimental implementations of the algorithms on a hard disk drive servo mechanism that is subjected to periodic disturbances known as repeatable runout.

Active control for vehicle interior noise using the improved iterative variable step-size and variable tap-length LMS algorithms

2019 ◽  
Vol 67 (6) ◽  
pp. 405-414 ◽  
Author(s):  
Ningning Liu ◽  
Yuedong Sun ◽  
Yansong Wang ◽  
Hui Guo ◽  
Bin Gao ◽  
...  
Keyword(s):  
Steady State ◽  
Noise Control ◽  
Convergence Speed ◽  
Interior Noise ◽  
Lms Algorithm ◽  
Variable Step Size ◽  
Step Size ◽  
Vehicle Interior ◽  
Vehicle Interior Noise ◽  
Variable Step

Active noise control (ANC) is used to reduce undesirable noise, particularly at low frequencies. There are many algorithms based on the least mean square (LMS) algorithm, such as the filtered-x LMS (FxLMS) algorithm, which have been widely used for ANC systems. However, the LMS algorithm cannot balance convergence speed and steady-state error due to the fixed step size and tap length. Accordingly, in this article, two improved LMS algorithms, namely, the iterative variable step-size LMS (IVS-LMS) and the variable tap-length LMS (VT-LMS), are proposed for active vehicle interior noise control. The interior noises of a sample vehicle are measured and thereby their frequency characteristics. Results show that the sound energy of noise is concentrated within a low-frequency range below 1000 Hz. The classical LMS, IVS-LMS and VT-LMS algorithms are applied to the measured noise signals. Results further suggest that the IVS-LMS and VT-LMS algorithms can better improve algorithmic performance for convergence speed and steady-state error compared with the classical LMS. The proposed algorithms could potentially be incorporated into other LMS-based algorithms (like the FxLMS) used in ANC systems for improving the ride comfort of a vehicle.

A noise resilient variable step-size LMS algorithm

2008 ◽  
Vol 88 (3) ◽  
pp. 733-748 ◽  
Author(s):  
Márcio Holsbach Costa ◽  
José Carlos Moreira Bermudez
Keyword(s):  
Lms Algorithm ◽  
Variable Step Size ◽  
Step Size ◽  
Variable Step

Improved stability performance of a feedback active noise control using a Steiglitz-McBride adaptive notch filter and robust secondary path identification based on variable step size Griffiths LMS algorithm

2021 ◽  
Vol 69 (2) ◽  
pp. 136-145
Author(s):  
S. Roopa ◽  
S.V. Narasimhan
Keyword(s):  
Noise Control ◽  
Active Noise Control ◽  
Notch Filter ◽  
Lms Algorithm ◽  
Variable Step Size ◽  
Step Size ◽  
Adaptive Notch Filter ◽  
Active Noise ◽  
Variable Step ◽  
Feedback Active Noise Control

A stable feedback active noise control (FBANC) system with an improved performance in a broadband disturbance environment is proposed in this article. This is achieved by using a Steiglitz-McBride adaptive notch filter (SM-ANF) and robust secondary path identification (SPI) both based on variable step size Griffiths least mean square (LMS) algorithm. The broadband disturbance severely affects not only FBANC input synthesized but also the SPI.TheSM-ANFestimated signal has narrowband component that is utilized for the FBANC input synthesis. Further, the SM-ANF error has broadband component utilized to get the desired signal for SPI. The use of variable step size Griffiths gradient LMS algorithm for SPI enables the removal of broadband disturbance and non-stationary disturbance from the available desired signal for better SPI. For a narrowband noise field, the proposed FBANC improves the convergence rate significantly (20 times) and the noise reduction from 10 dB to 15 dB (50%improvement) over the conventional FBANC (without SM-ANF and variable step size Griffiths LMS adaptation for SPI).

Application of Improved LMS Adaptive Algorithm in Acoustics Pyrometry

2014 ◽  
Vol 672-674 ◽  
pp. 2025-2028
Author(s):  
Shi Ping Zhang ◽  
Guo Qing Shen ◽  
Lian Suo An
Keyword(s):  
Temperature Measurement ◽  
Discrete Cosine Transform ◽  
Time Delay Estimation ◽  
Lms Algorithm ◽  
Variable Step Size ◽  
Least Mean Square ◽  
Step Size ◽  
Boiler Furnace ◽  
Cosine Transform ◽  
Variable Step

Acoustic pyrometry is a comparatively advanced method of temperature measurement developed in recent years, which possesses the essential characteristics of traditional temperature measurement approach. Considering the interferences, like strong background noise, reverberation and so on, in boiler furnace, the LMS (least mean square) adaptive filter algorithm should be improved to meet certain environment above. In order to make the LMS algorithm have the characteristic of fast convergence and small steady state error, an improved, power-normalized and variable step-size discrete cosine transform LMS algorithm is proposed, which combines the power-normalized discrete cosine transform LMS algorithm with the variable step size LMS algorithm that uses the sliding forgetting-weighted window. The time delay estimation simulation in the strong-noise environment verifies the improved DCT-MVSS LMS algorithm can achieve good performance.

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