Modeling and compensation of nonlinearities and friction in a micro hard disk drive servo system with nonlinear feedback control

Abstract

Friction and nonlinearities result in large residual errors and deteriorate the performance of head positioning of hard disk drive (HDD) servo systems and other mechanical servo systems. Thus, it is highly desirable to characterize the behaviors of nonlinearities and friction in the servo systems. This paper presents a fairly comprehensive modeling and compensation of friction and nonlinearities of a typical voice-coil-motor (VCM) actuator used in commercial HDDs, and the design of an HDD servo system using an enhanced nonlinear control technique. Our contributions are two-fold: We will first obtain a complete model of the VCM actuator including friction and nonlinear characteristics through a careful examination of the configuration and structure of the actual system and through a thorough analysis of its physical effects together with its time-domain and frequency-domain responses. We will then proceed to design a servo system for the hard drive using an enhanced composite nonlinear feedback (CNF) control technique with a simple friction and nonlinearity compensation scheme. The enhanced CNF technique has a feature of removing the uncompensated portion of friction and nonlinearities without sacrificing the overall tracking performance. Simulation and experimental results for both the modeling and the servo design show that our approach is very effective and successful. In particular, our experimental results show that the enhanced CNF control has outperformed the conventional proportional-integral-derivative (PID) control in settling time by 76%. We believe that this approach can be adopted to solve other servomechanism problems.

An Enhanced Robust Control Algorithm Based on CNF and ISM for the MEMS Micromirror against Input Saturation and Disturbance

“…It also determines the magnitude of r that can be tracked by such a control law without exceeding the control limit [17]. …”

“…It is clear that the boundedness of $x_d$ is equivalent to the stability of the closed-loop system (Equation (2)) with the CNF control law (Equation (12)) in the absence of disturbances w and input saturation, and it has been proved in [17]. …”

“…Therefore, it is possible for the CNF technique to simultaneously achieve quick response and negligible overshoot. The CNF technique has also been implemented in various of engineering applications such as hard disk drive servo systems [15,16,17], helicopter flight control systems [18,19], position servo systems [20,21], and grid-connected voltage source inverters [22]. …”

“…However, disturbances are non-negligible in practical environments, especially for the problems in high-precision control fields. Thus, both the enhanced composite nonlinear feedback and robust composite nonlinear feedback techniques are formulated to deal with constant disturbances [17,21]. Without considering input saturation, robust design for CNF technique has also been achieved by improving the nonlinear part to deal with unmodelled dynamic effects [23].…”

Neural-Based Compensation of Nonlinearities in an Airplane Longitudinal Model with Dynamic-Inversion Control

“…These functions, ρ V and ρ h , change from 0 to the large negative numbers as the tracking error approaches zero [23]. At the initial condition, when controlled outputs e V and e h are far from the step commands, ρ V and ρ h are small because the influence of these nonlinear portions is constrained.…”