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In this paper, we study the limitations of scheduling an internal model to reject disturbances with a time-varying frequency. Hence, any adaptive method that uses scheduling and frequency estimation is also limited in the same manner. The limitations of scheduling are to investigate by posing and solving the problem of rejecting periodic disturbances from a multichannel system when the frequencies of the periodic disturbances are changing rapidly in time by designing an scheduled controller that satisfies the internal model principle. The periodic disturbances are modeled by a sum of sinusoids and the frequencies of the disturbances are used for scheduling the controller. It is shown that a controller that regulates input additive disturbances may not regulate the same disturbances added to the output of the system. This is in contrast to the classical case where the frequency of the disturbances is constant. Copyright © 2011 John Wiley & Sons, Ltd.

Active noise control Feedforward control Parameter estimation Digital filters Control applications a b s t r a c t This paper discusses the design methodology for the active noise control of sound disturbances in a forced-air cooling system. The active sound cancellation algorithm uses the framework of output-error based optimization of a linearly parametrized filter for feedforward sound compensation to select microphone location and demonstrate the effectiveness of active noise cancellation in a small portable data projector. Successful implementation of the feedforward based active noise controller on a NEC LT170 data projector shows a 20–40dB reduction per frequency point in the spectrum of external noise of the forced-air cooling system can be obtained over a broad frequency range from 1 to 5kHz. A total noise reduction (unweighted) of 9.3dB is achieved.

In this paper, we consider the iterative learning control (ILC) framework to design a reference signal that directly cancels periodic disturbances in a feedback measurement. Cancellation of periodic disturbances is useful in reducing undesirable repeatable tracking errors in applications such as the two-stage servo track writing process for disk drives. A general problem description is given for a linear discrete-time periodic system and convergence results for the learning system are derived. A learning filter is designed with the use of a finite-impulse response model approximation for the inverse of the closed-loop sensitivity such that convergence is achieved in learning a reference signal that provides cancellation with periodic perturbations affecting the system measurement. The ILC algorithm is applied to a disk drive system where experimental results demonstrate the effectiveness of the method in reducing periodic measurement disturbances.

The basic principle of feedforward noise cancellation for broadband active noise reduction is based on the availability of a reliable measurement of the noise source. Reliability is compromised in case the noise measurement is acoustically coupled to the actual active noise cancellation (ANC), as stability and performance of the feedforward compensation becomes ambiguous. This paper presents a framework to recursively estimate a feedforward filter in the presence of acoustic coupling, addressing both stability and performance of the active feedforward noise cancellation algorithm. The framework is based on fractional model representations in which a feedforward filter is parameterized by coprime factorization. Conditions on the parameterization of the coprime factorization formulated by the existence of a stable perturbation enables stability in the presence of acoustic coupling. In addition, the paper shows how the stable perturbation can be estimated on-line via a recursive least-squares estimation of a generalized FIR filter to improve the performance of the feedforward filter for ANC.

This paper details the design of an adaptive internal model-based controller to attenuate periodic disturbances in the presence of random noise. The internal model-based controller is designed in two steps, making use of the separation principle to design a controller with the desired properties that stabilizes the closed-loop system. Periodic disturbances appear as harmonics of a fundamental frequency. The fundamental frequency of the disturbance is estimated with a magnitude/phase-locked loop and is used to adjust the parameters of the controller, specifically the natural frequency of the internal model and the feedback gain. An active noise control study shows the ability of the proposed method to cancel time varying disturbances in an acoustic system.

To achieve frequency separation between actuators of a dual-stage servo actuator system in a hard disk drive, the PQ control design method can be used. In the PQ method, the servo controller is designed by focusing on structural interference of the actuators. This paper provides a specific parametrization for fixed order feedback controllers used in the PQ-method for which the structural interference between actuators can be minimized. The proposed control design method is applied to a dual-stage instrumented suspension, where the additional sensor of the instrumented suspension is used to attenuate high frequency disturbance caused by windage turbulence in a hard disk drive.

In this paper a method is proposed to design an optimal controller that uses an internal model and an additive noise model to reject periodic disturbances. The proposed design method allows for the design of a feedback controller that rejects periodic disturbances in the presence of random noise. An active noise cancellation application for an HP DL380 G3 rack server cooling fan is presented to demonstrate the efiectiveness of the proposed design method. System identiflcation techniques are used to flnd a model of the non-periodic disturbances. The feedback controller was implemented in real-time to show the efiectiveness of periodic blade pass frequency sound reduction. Copyright c ∞ 2005 IFAC.

A feedforward control algorithm for active noise control based on the recursive estimation of a generalized finite impulse response (FIR) filter is presented in this paper. Recursive least square estimation (RLSE) with variable forgetting factors is applied to a commercial air ventilation silencer to provide the online estimation of the generalized finite impulse response (FIR) filter to obtain active noise compensation in an airduct. The advantage of the generalized FIR filters lies in the possibility to include prior knowledge of system dynamics in the tapped delay line of the filter. It is shown that a significant improvement in noise cancellation is obtained with the implementation of generalized FIR filter for feedforward ANC.

This paper summarizes the organization of a graduate course on control related topics in identification. The course is taught at the department of Mechanical and Aerospace Engineering at the University of California, San Diego and analyzes the problems of estimation on closed-loop data and control relevant approximation of systems. As part of the course, several case studies are reviewed and include the well documented examples of a sugar cane crushing mill and the identification of the marginally stable electromechanical system found in a CD-ROM player.

In this paper, we consider the problem of estimating low order and control relevant models of plant dynamics and additive noise dynamics on the basis of closed-loop experiments. Estimating low order models for both the plant and noise dynamics is important in control design applications that focus on disturbance rejection. Several methods for low order model estimation on the basis of closed-loop data exist in the literature, but fail to address the simultaneous estimation of low order noise models that are relevant in disturbance control problems. In this paper we evaluate and compare some of these methods and propose a new methodology that extends the results to low order noise model estimation. The new methodology is an extended two-stage method where the first stage is used to estimate high order models for filtering purposes. In the second stage, filtered signals are used for low order model approximation. The methodology is illustrated in a realistic simulation study based on the windage disturbance reduction of a flexible hard disk drive suspension.

This article presents identification algorithms dedicated to the modal analysis of civil aircraft structures during in-flight flutter tests. This particular operational framework implies several specifications for the identification procedure. To comply with these requirements, the identification problem is formulated in the frequency domain as an output-error problem. Iterative identification methods based on structured matrix fraction descriptions are used to solve this problem and to identify a continuous-time model. These iterative methods are specifically designed to deal with experiments where short-duration tests with multiple-input excitations are used. These algorithms are first discussed and then evaluated through a simulation example illustrative of the in-flight modal analysis of a civil aircraft. Based on these evaluation results, an efficient iterative algorithm is suggested and applied to real flight-test data measured on board a military aircraft.

We present a data-based approach for modeling and controller design of a dual-stage tape servo actuator. Our method uses step response measurements and a generalized realization algorithm to identify a multivariable discrete-time model of the actuator. The data acquisition and modeling can be implemented in the servo firmware of a tape drive. We have designed a dual-stage controller, based on the model, using loop shaping techniques adopted for multivariable control problems. We applied the procedure to the prototype of a dual-stage actuator tape head to reduce the effect of lateral tape motion. The prototype consists of a conventional voice coil motor for coarse positioning and a micro-actuator for fine positioning. The micro-actuator, which is mounted on the voice coil motor, uses a piezo crystal to follow high-frequency lateral tape motion (up to the kilohertz regime), while the voice coil motor follows only low-frequency lateral tape motion. Compared to a single-stage design, the dual-stage servo design provides a 25% bandwidth improvement and a voice coil motor control signal that is much smaller in magnitude.

In this study we consider the iterative learning control (ILC) framework to design a reference signal that reduces the periodic component of disturbances in a feedback measurement containing both repeatable and non-repeatable components. Reduction of periodic disturbances is useful in alleviating undesirable repeatable tracking errors in applications such as the two-stage servo track writing process for disk drives. A general problem description is given for a linear discrete time system and convergence robustness results for the learning system are derived. A learning filter is designed with the use of an FIR model approximation for the inverse of the closed-loop sensitivity for fast nominal convergence while robustness to modeling errors and non-repeatable disturbances is achieved through additional filtering. The ILC algorithm is applied to a disk drive system where experimental results demonstrate the effectiveness of the design method in reducing periodic measurement disturbances.

The increase in aerial storage capacities of future magnetic hard disk drives has fostered the use of dual-stage actuators for high track density data recording. In a hard disk drive with a dual-stage actuator the standard rotary actuation of the voice coil motor is combined with an additional micro or milli actuation to accomplish high-bandwidth and highly accurate track following. In order to guarantee error less data transfer, the track following servo controller needs to perform robustly under different operating conditions, that include changes in flying height and product manufacturing tolerance of the dual-stage actuator. Essential in the controller design is to characterize these uncertain conditions and design a robust track following servo accordingly. In this paper we present an experiment based methodology to characterize the varying servo conditions in the form of an uncertainty model. The uncertainty model can be used for analysis and synthesis of robust servo controllers.

In this paper, a scheduled controller is presented by the merging together of internal model-based control and linear parameter-varying control theory. The internal model is used to attenuate periodic disturbances and concepts from linear parameter-varying control theory are used to design the feedback gain that quadratically stabilizes the closed loop system during scheduling. An estimate of the frequency of the disturbance is used as the scheduling variable that updates the internal model. The order of the controller is kept low by making use of the separation principle and designing a reduced order observer for state feedback. A design example of a simple mass-spring-damper system demonstrates the effectiveness of the controller to cancel periodic disturbances with a time-varying frequency.

This paper presents the results of a parametric identification method for the modeling of the dynamics of a servo actuator and the windage disturbance present in a hard disk drive. The results are obtained with an identification method that is based on a recently introduced extended two-stage method, which enables the estimation of low order complexity models of system and disturbance dynamics on the basis of closed-loop data. As a result, experimental data obtained under realistic servo conditions is used to find low order discrete time models that describe the actuator and windage disturbance dynamics at different locations on the hard disk.

A feedforward control algorithm for active noise control based on the recursive estimation of a generalized finite impulse response (FIR) filter is presented in this paper. The feedforward control algorithm is applied to a commercial air ventilation silencer to provide active noise compensation in an airduct. A generalized FIR filter has the same linear parameter structure as a taped delay FIR filter that is favorable for (recursive) estimation purposes. However, the advantage of the generalized FIR filters lies in the possibility to include prior knowledge of system dynamics in the tapped delay line of the filter. By comparison with a conventional FIR filter implementation it is shown that a significant improvement in noise cancellation is obtained.

This paper addresses the problem of checking the consistency of experimental closed-loop frequency-domain data with uncertainty models that are structured using coprime factorizations. The uncertainty models presented in this paper use the knowledge of a stabilizing feedback controller to structure and formulate the uncertainty on a model. Subsequently, the controller dependent coprime factor uncertainty model can be used to formulate model (in)validation tests on the basis of closed-loop data. The model (in)validation is performed on sample data from a flexible structure to illustrate the presented model validation results. An open-loop based uncertainty model is also used to demonstrate the benefits of closed-loop uncertainty modeling over open-loop uncertainty modeling.

This paper presents a new methodology for feedforward filter design in active noise cancellation in the presence of acoustic coupling. This is done via a feedforward filter estimation that uses a dual-Youla parametrization to incorporate the acoustic coupling. The experimental results show that the feedforward filter parametrized and estimated via dual-Youla parametrization provides an effective feedforward compensation for the active noise control in an airduct.

Recently introduced methods of iterative identification and control design are directed towards the design of high performing and robust control systems. These methods show the necessity of identifying approximate models from closed loop plant experiments. In this paper a method is proposed to approximately identify normalized coprime plant factors from closed loop data. The fact that normalized plant factors are estimated gives specific advantages both from an identification and from a robust control design point of view. It will be shown that the proposed method leads to identified models that are specifically accurate around the bandwidth of the closed loop system. The identification procedure fits very naturally into the iterative identification/control design scheme as presented by Schrama (1992). >

Generally, fault detection is the process of monitoring a physical dynamic system accompanied by conformation and assessment of any degradation of system performance. These systems are modelled and terms that are representative of a specific fault are identified and monitored for detection. In this paper, a fault detection algorithm is developed to isolate and detect friction changes in a high precision positioning mechanism. The designed fault detection algorithm addresses dynamic model estimation, dynamic filtering and recursive parameter estimation techniques to monitor online friction changes. The procedure is illustrated on a high precision servo pneumatic cylinder that drives a translational air bearing apparatus, designed to permit the addition of friction. Side loading of the cylinder rod induced by a friction fault causes significant loss of performance in these applications. It therefore serves to design a simple and effective online fault detection and isolation scheme for the designed experimental set-up.

Crucial to the increase in aerial densities of future hard disk drives (HDD) is the increase of the number of tracks per inch. In order to achieve very high track densities new high bandwidth and very accurate servo systems will be necessary. One possible solution is the use of dual-stage actuators, in which a high bandwidth and a highly accurate micro-actuator (MA) is used in combination with a traditional voice coil motor (VCM). In this case the nature of the servo controller becomes multivariable since both the VCM and the MA have to be controlled simultaneously. The design of servo controllers for track following with dual-stage actuators has been an active area of research in the last few years. Modern control methods were specifically developed for multivariable systems and offer significant advantages over classical control methods. On the down side, they usually lead to controllers which are of order equal to or greater than the plant they were designed for. The aim of the paper is to present a systematic approach for the design of a fixed order servo controller and to illustrate this design on a piezoelectric MA designed by Hutchinson Technologies Inc. The complexity of the servo controller is limited to address costs and implementation issues in a commercial HDD. The systematic approach for such a low order servo controller design is developed in the paper by utilizing H/sub /spl infin//-optimization with a choice of specific closed loop weighting functions and additional constraints on the order of the controller.

This paper discusses the approximation and feedback relevant parametric identification of a positioning mechanism present in a wafer stepper. The positioning mechanism in a wafer stepper is used in chip manufacturing processes for accurate positioning of the silicon wafer on which the chips are to be produced. The accurate positioning requires a robust and high-performance feedback controller that enables a fast throughput of silicon wafers. A control relevant set of multivariable finite dimensional linear time invariant discrete-time models is formulated and estimated on the basis of closed-loop experiments. The set of models is shown to be suitable for model-based robust control design of the positioning mechanism. This is illustrated by a successful design and implementation of a robust controller.

This Special Issue is a collection of papers that were presented at the 17th ASME Conference on Information Storage and Processing Systems (ISPS) at Santa Clara University, Santa Clara, CA, USA on June 18 and 19, 2007. To archive the papers presented at this 17th ISPS conference, all authors of papers submitted to the conference were encouraged to submit a full paper to this Special Issue in Microsystems Technologies. The papers that appear in this Special Issue have been subjected to a rigorous peer-review process in which many contributions had to be revised substantially before they could be published in this Special Issue. Obviously, this process has created a special selection of the many topics presented at the 17th ISPS conference, making it a great privilege to host the 17th ISPS conference and serve as guest editors for this Special Issue. The ISPS division of the ASME is the main division working on storage systems that include disk drives, tape drives, and optical drives. The ISPS division has held their annual conference at Santa Clara University in sunny California in June of each year and provides an environment in which researchers of both academic and industrial backgrounds share their latest developments on data storage systems. Since 2003, tri-annually, the ISPS division joins forces with the IIP (Information, Intelligent, and Precision Machines) division of the JSME (Japanese Society of Mechanical Engineers) to organize a joint conference called MIPE (Micromechatronics for Information and Precision Equipment). The annual conference of the ISPS division of the ASME is a very unique conference that brings together academia and industry in joint sessions on topics that relate to the interdisciplinary nature of the research in data storage and processing systems. To achieve the goal of merging academic and industrial research topics, the ISPS conference is held at Santa Clara in the Silicon Valley, allowing local industrial participants to attend and contribute to the conference with little travel time. With easy international access to the Bay area, the conference also enjoys many international visitors. The ISPS conference promotes industry and academic interaction by an organization that features many interdisciplinary technical sessions with a specific application focus. At the 17th ISPS conference eight different technical sessions were organized, each with dedicated session chairs to solicit papers and contributions from both academic and industrial institutions. The technical sessions at the 17th ISPS conference included Actuators and Suspensions with applications in actuator and (dual-stage) suspension design, dynamics and analysis; Servo Control and Servo Technology: bringing together topics on dynamics, vibrations, servo design, servo writing, tracking and seeking; Tribology and Head/ Media Interface: with contributions on friction, wear, lubrication, corrosion, contamination, thin films, contact mechanics and heat transfer. Spindle Motor and Acoustics: with contemporary issues on design, vibrations, acoustics and tribology related aspects of spindle motors; Flexible Media Mechanics and Tape Storage: illustrating the issues R. A. de Callafon (&) Department of Mechanical and Aerospace Engineering, Jacobs School of Engineering, UC San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0411, USA e-mail: callafon@ucsd.edu