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.
This paper studies possible robust control design methods in triple-stage actuation settings for achieving minimum position error signal (PES) while maintaining enough stability margins. Firstly, the sensitivity-decoupling design technique, is utilized to estimate the resulting increase in low frequency disturbance attenuation and servo bandwidth. A systematic tuning methodology based on μ-synthesis is then proposed for track-following servo design of triple-stage actuation systems. In this approach, the objective is to minimize the PES, by considering all constraints and uncertainties explicitly in the design. We describe a step by step Multi-Input Single-Output (MISO) controller design methodology which includes system modeling, noise characterization, control objective determination and controller synthesis and verification. In this methodology, servo bandwidth is not the only performance metric. Rather, the control objective will be to minimize the closed-loop system H∞ norm directly, while all stroke and control constraints are satisfied and enough stability margin is ensured. The proposed method is applied to design track-following feedback controllers for single-, dual- and triple-stage actuation systems. Simulation results show that compared to dual-stage actuation, triple-stage actuation enhances low frequency disturbance rejection by 6 dB at around 100Hz and increases servo bandwidth from ∼3kHz to ∼5kHz.
This paper considers robust controller design for track-following in hard disk drives (HDD) with irregular sampling of the position error signal (PES) but regular (clock-driven) control updates. This sampling and actuation behavior is modeled by applying a novel discretization method to a continuous-time model of an HDD, resulting in a discrete-time linear periodically time-varying model. Then, the controller design is performed using optimal control for periodic systems and uses a generalization of the disk margin to quantify the robustness of the closed-loop system. To show the effectiveness of the proposed method, the design methodology is applied to a hard disk drive model and the resulting controller is validated by examining its nominal performance in terms of the root mean square of the standard deviation of the PES and robustness in terms of disk margin. Since the proposed controller has too many parameters to be implementable on an HDD due to memory limitations, we use a vector quantization method to approximate the entire parameter set of the designed controller by a smaller set of parameters.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.