An Adaptive Feedforward Control Approach for Rejecting Disturbances Acting on Uncertain Linear Systems

This paper proposes a novel adaptive feedforward control method for rejecting unknown disturbances acting on linear systems with uncertain dynamics. The proposed algorithm does not require a model of the plant dynamics and does not use batches of measurements in the adaptation process. Moreover, it is applicable to both minimum and non-minimum phase plants. The algorithm is a “direct” adaptive method, in the sense that the identification of system parameters and the control design are performed simultaneously. In order to verify the effectiveness of the proposed method, an adaptive feedforward controller is designed as an add-on compensator to the existing baseline controller of a hard disk drive. An accelerometer mounted on the disk drive casing provides the input signal for the controller. The control objective is to minimize the standard deviation of the position error signal in the presence of external random vibrations. Simulation results show that reduction of 46% in the standard deviation of the position error signal can be obtained.

Low SNR Signal Processing for Head Media Contact Detection in HDD

The methodology for processing grossly undersampled HDD position error signal (PES) is proposed to improve the head-disk contact detection process. The proposed method is a combination of compressive sampling (CS) and adaptive discrete wavelet transform (ADWT) techniques. Here, CS is employed to reconstruct the PES information from very few revolutions of data while ADWT is utilized for extracting head-disk interface (HDI) modulation changes during thermal protrusion of the read/write element.

An Improved Digital Servo Burst Signal Sampling Model for Disk Drives

In order to calculate the servo position error signal (PES) in the servo system, it is necessary to make high precision sampling and FFT calculation for the burst signal. Most designer s adopt 8bits ADC converter in the read write channel servo system of hard drive controller chip 88i6310 to cost down, and both servo system and signal system share the sampling circuit. Because of the quantitative noise disturbing during the sampling process, it is not enough to use 6bits ADC converter for the serve burst signal, and significant error exist for t he burst signal with the FFT calculation. This paper analyzed the existing servo over-sampling model via quantitative error model firstly, and provided the enhanced servo system sampling model. The simulation shows that, the enhanced solution reduces the average quantitative error from 0. 38 LSB to 0.14LSB, and improves the resolution of ADC converter from 9.5 bits to 10.8 bits.