Publications

Owing to the explosive advancements in recent years in the areas of computational intelligence, material synthesis, and device integration, a new era of intelligent robotics, featuring unprecedented capabilities of sensing, actuation, and decision making, has arrived. Various newly developed robotic systems have penetrated into virtually all industrial sectors, ranging from manufacturing, energy, aerospace and naval, infrastructure, to health care and service, etc. They possess remarkably enhanced performances in terms of accuracy, adaptivity, reliability, and autonomy, and are poised to change fundamentally our modalities of working and living. The new accomplishments exemplify the collaborative efforts by academia and industry that are currently accelerating. Aiming at documenting and disseminating the progresses and identifying growth opportunities, this “Focused Section on Machine Learning, Estimation and Control for Intelligent Robotics” of the International Journal of Intelligent Robotics and Applications (IJIRA) showcases a number of recent technological achievements in the learning and control of robotic systems. It includes nine papers that share the common theme of robotic systems utilizing complex or heterogeneous data in their design and control through advanced learning and estimation techniques.

Closed-loop disturbance rejection without sacrificing overall system performance is a fundamental issue in a wide range of applications from precision motion control, active noise cancellation, to advanced manufacturing. At the core of rejecting band-limited disturbances is the shaping of feedback loops to actively and flexibly respond to different disturbance spectra. However, such strong and flexible local loop shaping has remained underdeveloped for systems with nonminimum-phase zeros due to challenges to invert the system dynamics. This paper proposes a local loop shaping with prescribed performance requirements in systems with nonminimum-phase zeros. Pioneering an integration of the interpolation theory with a model-based parameterization of the closed loop, the proposed solution provides a filter design to match the inverse plant dynamics locally and as a result, creates a highly effective framework for controlling both narrow- and wide-band vibrations. From there, we discuss methods to control the fundamental waterbed limitation, verify the algorithm on a laser scanning platform in selective laser sintering additive manufacturing, and compare the benefits and tradeoffs over con- ventional direct inverse-based loop-shaping method. The results are supported by both simulation and experimentation.

Like other consumer products such as automobiles, selective laser sintering (SLS) additive manufacturing (AM) systems age in they lifespan – degradations of system components and materials hinder consistent outcome of the manufacturing process. Despite significant tool development, laser interactions with light-color materials challenge in-situ monitoring to properly capture the complex process physics, and data analytics to fully understand process degradation does not yet exist. The objective of this presentation is to discuss a sensing and data processing towards consistent and repetitive AM in presence of system degradation. We present an optical design to image the interaction between laser and Polyamide 12 (PA12) powders at different stages of system and material degradation. Pioneering a data analytics with morphological image processing, field correction, and particle analysis on the developed database, we address key issues induced by contaminated optics, spatters, and smokes to isolate the heat-affected zone (HAZ) from the noisy gray-scale raw images. From there, we analyze the morphology of the extracted area and identify signatures for process defects such as balling, overheating, and lack of sintering. These defects are further used to characterize process disturbances in presence of system degradation, bridging the gap between spatial-resolved process monitoring and our ultimate goal of model-based control for a robust, high-throughput AM.

A considerable amount of expensive materials remain un-joined in selective laser sintering (SLS) additive manufacturing (AM) that generates complex metallic and high-performance polymeric parts from micrometer-diameter powders. Such materials, particularly the ones near the heat affected zone (HAZ), go through irreversible chemical degradations originated from thermal and laser-induced oxidations. In the SLS of polyamide 12 (PA12), despite efforts in understanding the degradation mechanisms of the materials, existing aging models center on thermal-induced oxidation. How to model fully material degradation in the complex SLS has remained not well understood. In this work, we propose a first-instance kinetic model considering both thermal and laser-induced oxidations to predict the degradation rate of polyamide 12 in SLS. By data-driven fitting of the laser-induced degradation into the kinetics of oxidation, the proposed model can predict the oxidation rates using two easily available parameters: materials density and oxidation time. The predicted oxidation matches on average 89.53% with results from experimentations, in contrast to a 34.48% accuracy from a conventional aging model. Furthermore, the new model applies to not only pure materials but also composite powders with mixed pure and recycled PA12 materials, making it adaptable to more complex material recycling configurations.

This paper provides a control method for autonomously tracking moving targets with slow and delayed visual feedback. Such capabilities underpin robotic applications ranging from transportation to medical systems. Compared to classic position-based visual servo, the proposed approach achieves 95% reduction of tracking errors when partial knowledge of the target dynamics is known. The result is achieved via a tripartite approach including (1) a velocity control of the robot that ensures exponential reduction of the visual feature error even subject to a maneuvering target, (2) a pose and velocity estimation that considers the dynamics of the moving target, and (3) a multirate information recovery that recovers fast motion estimates from slow and delayed visual feedback.

A high-precision additive manufacturing (AM) process, powder bed fusion (PBF) has enabled unmatched agile manufacturing of a wide range of products from engine components to medical implants. While finite element modeling and closed-loop control have been identified key for predicting and engineering part qualities in PBF, existing results in each realm are developed in opposite computational architectures wildly different in time scale. This paper builds a first-instance closed-loop simulation framework by integrating high-fidelity finite element modeling with feedback controls originally developed for general mechatronics systems. By utilizing the output signals (e.g., melt pool width) retrieved from the finite element model (FEM) to update directly the control signals (e.g., laser power) sent to the model, the proposed closed-loop framework enables testing the limits of advanced controls in PBF and surveying the parameter space fully to generate more predictable part qualities. Along the course of formulating the framework, we verify the FEM by comparing its results with experimental and analytical solutions and then use the FEM to understand the melt-pool evolution induced by the in- and cross-layer thermomechanical interactions. From there, we build a repetitive control (RC) algorithm to attenuate variations of the melt pool width.

Temporal sensor management for sparse information retriveal.

This paper provides a control method for autonomously tracking moving targets with slow and delayed visual feedback. Such capabilities underpin robotic applications ranging from transportation to medical systems. Compared to classic position-based visual servo, the proposed approach achieves 95% reduction of tracking errors when partial knowledge of the target dynamics is known. The result is achieved via a tripartite approach including (1) a velocity control of the robot that ensures exponential reduction of the visual feature error even subject to a maneuvering target, (2) a pose and velocity estimation that considers the dynamics of the moving target, and (3) a multirate information recovery that recovers fast motion estimates from slow and delayed visual feedback.

Large-scale wind turbines usually operate in turbulent wind fields. During turbine operation, periodic loads on blades are induced by wind shear, tower shadow effects and centrifugal forces. While collective pitch control (CPC) is unable to deal with periodic loads, the advent of individual pitch control (IPC) provides opportunities to mitigate periodic loads. Nevertheless, difficulties in algorithm development remain. Most notably, wind turbine dynamics is highly nonlinear, and significant modeling uncertainties exist when the turbine operates away from the nominal operation point from which the linearized model is drawn. This paper presents a robust individual pitch control framework to reject periodic loads under model uncertainties. The multi-blade coordinate (MBC) transformation is employed to enable more accurate nominal model development. The turbine model includes horizontal and vertical shear disturbance components in addition to horizontal disturbance. The multivariable individual controller can reduce response peaks at high harmonic frequencies, and the coupling dynamics of three-bladed system is taken into account. The structured singular values ( )-synthesis approach is utilized to guarantee the robust stability and robust performance with respect to uncertainties. Case studies illustrate significant periodic load mitigation as well as fatigue alleviation in speed-varying wind fields.

As a powder bed fusion additive manufacturing (AM) process, selective laser sintering (SLS) has seen widespread use with unique advantages in achievable part complexity and processable materials. However, greater applications of SLS AM remain hindered by insufficient assurance of the part qualities. A major barrier to such long-felt but not fully realized quality assurance rises from challenges in sensing and control mechatronics in presence of the multi-scale laser-material interactions. This paper presents the design of a full-scale, fully-accessible polymer SLS testbed with tailored mechatronics for in-situ monitoring and controls. We discuss approaches for controlling key process parameters and for measuring process signatures that are crucial for next-generation assurance of part accuracy and quality. We validated these designs in actual 3D printing of nylon powders among a tested list of low- to high-temperature polymers. Along this process, we (1) test a new scanning control to address a salient challenge in maintaining melting pool properties within each layer, and (2) reveal the characteristics of optic contamination as a process disturbance.

Capable of building high-quality, complex parts directly from digital models, selective laser sintering (SLS) additive manufacture (AM) is a core method of agile manufacturing. Polyamide 12 is the most commonly and successfully used polymer powders to date in SLS due to the conforming thermal behaviors of this thermoplastic polymer. State of the art technology produces a substantial amount of un-sintered powders after the manufacturing process. Failure to recycle and reuse these aged powders not only leads to economic losses but also is environmentally unfriendly. This is particularly problematic for powders close to the heat-affected zones that go through severe thermal degradations during the laser sintering processes. Limited procedures exist for systematically reusing such extremely aged powders. This work proposes a new process control method to maximize reusability of aged and extremely aged polyamide 12 powders. Building on a previously untapped interlayer heating, preprocessing, and mixing of powder materials, we show how reclaimed polyamide 12 powders can be consistently reprinted into functional samples, with mechanical properties even superior to current industrial norms. In particular, the proposed method can yield printed samples with 18.04 percent higher tensile strength and 55.29 percwent larger elongation at break using as much as 30 percent of extremely aged powders compared to the benchmark sample.

Modulating the closed-loop transmission of energy in a wide frequency band without sacrificing overall system performance is a fundamental issue in a wide range of applications from preci- sion control, active noise cancellation, to energy guiding. This paper introduces a loop-shaping approach to create such wide- band closed-loop behaviors, with a particular focus on systems with nonminimum-phase zeros. By pioneering an integration of the interpolation theory with a model-based parameterization of the closed loop, the proposed approach creates a framework to shape energy transmission with user defined performance met- rics in the frequency domain. Application to laser-based pow- der bed fusion additive manufacturing validates the feasibility to compensate wide-band vibrations and to flexibly control system performance at other frequencies.

Plug-in or add-on control is integral for high- performance control in modern precision systems. Despite the capability of greatly enhancing the steady-state performance, add-on compensation can introduce output discontinuity and significant transient response. Motivated by the vast application and the practical importance of add-on control designs, this paper identifies and investigates how general nonsmoothness in signals transmits through linear control systems. We explain the jump of system states in the presence of nonsmooth inputs in add- on servo enhancement, and derive formulas to mathematically characterize the transmission of the nonsmoothness. The results are then applied to devise fast transient responses over the traditional choice of add-on design at the input of the plant. Application examples to a manufacturing control system are conducted, with simulation and experimental results that validate the developed theoretical tools.

This paper considers the real-time recovery of a fast discrete signal (e.g., updated every T seconds) by using sparsely sampled sensor measurements whose sampling intervals are much larger than T (e.g., MT and NT, where M and N are integers). Assuming the fast signal is an autoregressive process with known parameters, we propose an online information recovery algorithm that reconstructs the missing, fast time series by a complementary modulation of the sensor speeds MT and NT, and by a model-based fusion of the sparsely collected data. We provide the collaborative sensing design, parametric analysis, existence of solutions, and optimization of the algorithm. Application to a closed-loop disturbance rejection problem reveals the feasibility to reject fast disturbance signals fully with only slow sensors in real time, and in particular, the rejection of narrow-band disturbances whose frequencies are much higher than the Nyquist frequencies of the sensors.

This paper discusses fractional-order repetitive control (RC) to advance the quality of periodic energy deposition in laser-based additive manufacturing (AM). It addresses an intrinsic RC limitation when the exogenous signal frequency cannot divide the sampling frequency of the sensor, e.g., in imaging-based control of fast laser-material interaction in AM. Three RC designs are proposed to address such fractional-order repetitive processes. In particular, a new multirate RC provides superior performance gains by generating high-gain control exactly at the fundamental and harmonic frequencies of exogenous signals. Experimentation on a galvo laser scanner in AM validates effectiveness of the designs.

Performance of controls beyond the Nyquist frequency.

This paper studies control approaches to advance the quality of repetitive energy deposition in powder bed fusion (PBF) additive manufacturing. A key pattern in the nascent manufacturing process, the repetitive scanning of the laser or elec- tron beam can be fundamentally improved by repetitive control (RC) algorithms. An intrinsic limitation, however, appears in discrete-time RC when the exogenous signal frequency cannot divide the sampling frequency. In other words, N in the internal model 1/ 􏰊1 − z−N 􏰋 is not an integer. Such a challenge hampers high-performance applications of RC to PBF because periodicity of the exogenous signal has no guarantees to comply with the sampling rate of molten-pool sensors. This paper develops a new multirate RC and a closed-loop analysis method to address such fractional-order RC cases by generating high-gain control signals exactly at the fundamental and harmonic frequencies. The proposed analysis method exhibits the detailed disturbance- attenuation properties of the multirate RC in a new design space. Numerical verification on a galvo scanner in laser PBF reveals fundamental benefits of the proposed multirate RC.

This paper studies repetitive control (RC) algorithms to advance the quality of repetitive energy deposition in laser-based additive manufacturing (AM). An intrinsic limitation appears in discrete-time RC when the period of the exogenous signal is not an integer multiple of the sampling time. Such a challenge hampers high- performance applications of RC to laser-based AM because periodicity of the exogenous signal has no guarantees to comply with the sampling rate of molten-pool sensors. This paper investigates three RC algorithms to address such fractional-order RC cases. A wide-band RC and a quasi RC apply the nearest integer approximation of the period, yielding overdetermined and partial attenuation of the periodic disturbance. A new multirate RC generates high- gain control signals exactly at the fundamental frequency and its harmonics. Experimentation on a dual-axis galvo scanner in laser-based AM compares the effectiveness of different algorithms and reveals fundamental benefits of the proposed multirate RC.

A fundamental challenge in sampled-data control arises when a continuous-time plant is subject to disturbances that possess significant frequency components beyond the Nyquist frequency of the feedback sensor. Such intrinsic difficulties create formidable barriers for fast high-performance controls in modern and emerging technologies such as additive manufacturing and vision servo, where the update speed of sensors is low compared with the dynamics of the plant. This paper analyzes spectral properties of closed-loop signals under such scenarios, with a focus on mechatronic systems. We propose a spectral analysis method that provides new understanding of the time- and frequency-domain sampled-data performance. Along the course of uncovering spectral details in such beyond-Nyquist controls, we also report a fundamental understanding on the infeasibility of single-rate high-gain feedback to reject disturbances not only beyond but also below the Nyquist frequency. New metrics and tools are then proposed to systematically quantify the limit of performance. Validation and practical implications of the limitations are provided with experimental case studies performed on a precision mirror galvanometer platform for laser scanning.

Plug-in or add-on control is integral for high- performance control in modern precision systems. Despite the capability of greatly enhancing the steady-state performance, add-on compensation can introduce output discontinuity and significant transient response. Motivated by the vast application and the practical importance of add-on control designs, this paper identifies and investigates how general nonsmoothness in signals transmits through linear control systems. We explain the jump of system states in the presence of nonsmooth inputs in add- on servo enhancement, and derive formulas to mathematically characterize the transmission of the nonsmoothness. The results are then applied to devise fast transient responses over the traditional choice of add-on design at the input of the plant. Application examples to a manufacturing control system are conducted, with simulation and experimental results that validate the developed theoretical tools.

A robust individual pitch control strategy is presented to deal with periodic load disturbances on wind turbines under operating point variation. The asymmetric loads are mainly caused by the tower shadow and wind shear effects. Multi-blade coordinate (MBC) transformation is utilized to model the turbine dynamics under various operating points. The coupling dynamics of the multi-input multi-output (MIMO) system are considered to reveal high harmonic frequency peak reduction. The stability and robustness performance of the system under uncertainties are guaranteed by robust control design. The performance of the synthesized controller is compared with a collective controller and a PI individual controller. The results show significant load mitigation in periodic frequencies.

A fundamental problem arises in feedback control when the system is subject to fast disturbances but can only get slowly updated sensor feedback. The problem is particularly challenging when the disturbances have frequency components near or beyond the sensor’s Nyquist sampling frequency. Such difficulties occur to selective laser sintering, an additive manufacturing process that employs galvo scanners to steer high-power laser beams and relies on non-contact, slow sensing such as visual feedback to enhance the product quality. In pursuit of addressing the fundamental challenge in quality control under slow sensor feedback, this paper introduces a multi-rate control scheme to compensate beyond-Nyquist disturbances with application to selective laser sintering. This is achieved by designing a special bandpass filter with tailored frequency response beyond the slow Nyquist frequency of the sensor, along with integrating model-based predictor that reconstructs signals from limited sensor data. Verification of the algorithm is conducted by both simulation and experimentation on a galvo scanner that directs the energy beam in the additive manufacturing process.

The vision of sustainable mass customization calls for additive manufacturing (AM) processes that are resilient to process variations and interruptions. This work concerns a system-theoretical approach towards such a smart, reliable AM. Specifically, one focused example is laser-aided powder bed fusion for fabricating metallic and high-performance polymeric parts. By capitalizing on the fundamental precision heating and solidification, together with the layer-by-layer iterations of energy source, feedstock, and toolpath, we will discuss mathematical abstractions of process imperfections that understand the intricate thermomechanical interactions and are tractable under realtime computation budgets. A model-based decentralized sensing is then proposed to discard unnecessary information to make full use of data-intensive sensor sources like streaming videos. Finally, we discuss our results of controlling the proper energy deposition to ensure quality and reproducibility in a closed loop. Simulation and experimentation with industrial laser scanning and an in-house built PBF testbed validate the theoretic and algorithmic results.

A discrete-time backstepping control algorithm is proposed for reference tracking of sys- tems affected by both broadband disturbances at low frequencies and narrow band distur- bances at high frequencies. A discrete time DOB, which is constructed based on infinite impulse response filters is applied to compensate for narrow band disturbances at high fre- quencies. A discrete-time nonlinear damping backstepping controller with an augmented observer is proposed to track the desired output and to compensate for low frequency broadband disturbances along with a disturbance observer, for rejecting narrow band high frequency disturbances. This combination has the merit of simultaneously compensating both broadband disturbances at low frequencies and narrow band disturbances at high fre- quencies. The performance of the proposed method is validated via experiments.

This paper discusses fractional-order repetitive control (RC) to advance the quality of periodic energy deposition in laser-based additive manufacturing (AM). It addresses an intrinsic RC limitation when the exogenous signal frequency cannot divide the sampling frequency of the sensor, e.g., in imaging-based control of fast laser-material interaction in AM. Three RC designs are proposed to address such fractional-order repetitive processes. In particular, a new multirate RC provides superior performance gains by generating high-gain control exactly at the fundamental and harmonic frequencies of exogenous signals. Experimentation on a galvo laser scanner in AM validates e􏰆ffectiveness of the designs.

Nowadays, despite the emerging adoption of the solid state drives, hard disk drives (HDDs) are still used extensively as cost-effective and reliable solutions for data storage. In addition to its usual application in desktops and laptops, HDDs become the primary storage medium for the data centers. The track following control task in HDD requires that the read/write head be positioned over the data track center at nano-scale accuracy, which requires an error tolerance about 7nm. Therefore, the dual-stage HDD is introduced to enhance the HDD control performance for extended bandwidth and improved disturbance rejection.

Time-varying unknown wind disturbances significantly influence the dynamics of the wind turbines. In this paper, a disturbance observer based (DOB) control scheme is illustrated to reject disturbances to the wind turbines at above-rated wind speeds. Specifically, we aim at maintaining a constant output power and achieving better generator speed regulation when the wind turbine is operated at time-varying and turbulent wind fields. The inner DOB scheme is augmented with a collective gain-scheduling proportional integral (PI) feedback controller to asymptotically reject the persistent unknown time-varying disturbances. The proposed algorithm is applied to both linearized and nonlinear National Renewable Energy Laboratory (NREL) offshore 5-MW baseline wind turbines. Also an extra compensator to deal with the mismatch between the linearized reduced-order model and the actual nonlinear wind turbine is discussed. The novel application of the augmented DOB pitch controller demonstrates improved power and speed regulation in the above-rated region both for linearized and nonlinear plants.

Modern hard disk drive (HDD) systems are subjected to various external disturbances. One particular category, defined as wide-band disturbances, can generate vibrations with their energy highly concentrated at several frequency bands. Such vibrations are commonly time-varying and strongly environment/product-dependent; and the wide spectral peaks can occur at frequencies above the servo bandwidth. This paper considers the attenuation of such challenging vibrations in the track-following problem of HDDs. Due to the fundamental limitation imposed by the Bode’s Integral Theorem, the attenuation of such wide-band disturbances may cause unacceptable amplifications at other frequencies. To achieve a good performance and an optimal tradeoff, an add-on adaptive vibration-compensation scheme is proposed in this paper. Through parameter adaptation algorithms that online identify both the center frequencies and the widths of the spectral peaks, the proposed control scheme automatically allocates the control efforts with respect to (w.r.t) the real-time disturbance characteristics. The effect is that the position error signal (PES) in HDDs can be minimized with effective vibration cancellation. Evaluation of the proposed algorithm is performed by experiments on a Voice-Coil-Driven Flexible Positioner (VCFP) system.

Selective laser sintering (SLS) is an additive manufactur- ing (AM) process that builds 3-dimensional (3D) parts by scan- ning a laser beam over powder materials in a layerwise fashion. Due to its capability of processing a broad range of materials, the rapidly developing SLS has attracted wide research attention. The increasing demands on part quality and repeatability are urg- ing the applications of customized controls in SLS. In this work, a Youla-Kucera parameterization based forward-model selective disturbance observer (FMSDOB) is proposed for flexible servo control with application to SLS. The proposed method employs the advantages of a conventional disturbance observer but avoids the need of an explicit inversion of the plant, which is not al- ways feasible in practice. Advanced filter designs are proposed to control the waterbed effect. In addition, parameter adaptation algorithm is constructed to identify the disturbance frequencies online. Simulation and experimentation are conducted on a galvo scanner in SLS system.

This paper provides an optimization-based approach to assure the strict positive real (SPR) condition in a set of recursive parameter adaptation algorithms (PAA). The developed algorithms and tools enable a multi-objective formulation of the SPR problem, creating new controls of the stability and parameter convergence in PAAs. In addition to assuring the SPR condition for global stability in PAAs, we provide an algorithmic solution for uniform convergence under performance constraints in PAAs. Several new aspects of parameter convergence were observed with the adoption of the algorithm in a narrow-band identification problem. The proposed algorithm is verified in simulation and experiments on a precision motion control platform in advanced manufacturing.

A fundamental challenge in digital control arises when the controlled plant is subjected to a fast disturbance dynamics but is only equipped with a relatively slow sensor. Such intrinsic difficulties are, however, commonly encountered in many novel applications such as laser- and electron-beam-based additive manufacturing, human-machine interaction, etc. This paper provides a discrete- time regulation scheme for exact sampled-data rejection of disturbances beyond Nyquist frequency. By introducing a model-based multirate predictor and a forward-model disturbance observer, we show that the inter-sample disturbances can be fully attenuated despite the limitations in sampling and sensing. The proposed control scheme offers several advantages in stability assurance and lucid design intuitions. Verification of the algorithm is conducted on a motion control platform that shares the general characteristics in several advanced manufacturing systems.

A direct adaptive regulation scheme using an adaptive FIR Youla–Kučera Filter has been proposed for solving the EJC Benchmark on rejection of multiple unknown and time-varying narrow-band dis- turbances (Castellanos Silva et al., 2013 [4]). Despite excellent results, this approach requires a careful design of the central controller in terms of selection of some of the assigned closed-loop poles. A modified scheme is proposed in this paper which will incorporate a particular adaptive IIR Youla–Kučera Filter, called ρ-notch structure (the denominator is a projection inside the unit circle of the poles of the model of the disturbance which has roots on the unit circle). The adaptive scheme estimates separately the numerator and denominator parameters of the IIR Youla–Kučera Filter. Stability and convergence proofs are given along with simulation and real-time results. Comparison with results already obtained for the EJC Benchmark is provided. The use of this approach drastically simplifies the design of the central controller and provides even better results than (Castellanos Silva et al., 2013 [4]) with the advantage to use a single central controller independent of the number of narrow band disturbances.

A controller design is presented for directly shaping the sensitivity function in the feedback control of dual-input single-output (DISO) systems. We provide special forms of discrete-time Youla-Kucera (YK) parameterization to obtain stabilizing controllers for DISO systems, and discuss concepts to achieve a reduced-complexity formulation. The proposed YK parameterization is based on an inverse of the loop transfer function, which gives benefits such as clearer design intuition and reduced complexity in construction. The algorithm is verified by simulations and experiments on hard disk drive systems, with application to wideband vibration and harmonic disturbance rejections.

This paper discusses a discrete-time loop shaping algorithm for servo enhancement at multiple wide frequency bands. Such design considerations are motivated by a large class of practical control problems such as vibration rejection, active noise control, and periodical reference tracking; as well as recent novel challenges that demand new design in the servo technologies. A pseudo Youla–Kucera parameterization scheme is proposed using the inverse system model to bring enhanced control at selected local frequency regions. Design methodologies are created to control the waterbed amplifications that come from the fundamental limitations of feedback control. Finally, simulation and experimental verification are conducted in precision control and semiconductor manufacturing.

This paper discusses a discrete-time loop shaping algorithm for servo enhancement at multiple wide frequency bands. Such design considerations are motivated by a large class of practical control problems such as vibration rejection, active noise control, and periodical reference tracking; as well as recent novel challenges that demand new design in the servo technologies. A pseudo Youla–Kucera parameterization scheme is proposed using the inverse system model to bring enhanced control at selected local frequency regions. Design methodologies are created to control the waterbed amplifications that come from the fundamental limitations of feedback control. Finally, simulation and experimental verification are conducted in precision control and semiconductor manufacturing.

Vibrations with unknown and/or time-varying frequencies significantly affect the achievable performance of control systems, particularly in precision engineering and manufacturing applications. This paper provides an overview of disturbance-observer-based adaptive vibration rejection schemes; studies several new results in algorithm design; and discusses new applications in semiconductor manufacturing. We show the construction of inverse-model-based controller parameterization and discuss its benefits in decoupled design, algorithm tuning, and parameter adaptation. Also studied are the formulation of recursive least squares and output-error-based adaptation algorithms, as well as their corresponding scopes of applications. Experiments on a wafer scanner testbed in semiconductor manufacturing prove the effectiveness of the algorithm in high-precision motion control.

In repetitive control (RC), the enhanced servo performance at the fundamental frequency and its higher order harmonics is usually followed by undesired error amplifications at other frequencies. In this paper, we discuss a new structural configuration of the internal model in RC, wherein designers have more flexibility in the repetitive loop-shaping design, and the amplification of nonrepetitive errors can be largely reduced. Compared to conventional RC, the proposed scheme is especially advantageous when the repetitive task is subject to large amounts of nonperiodic disturbances. An additional benefit is that the transient response of this plug-in RC can be easily controlled, leading to an accelerated transient with reduced overshoots. Verification of the algorithm is provided by simulation of a benchmark regulation problem in hard disk drives, and by tracking-control experiments on a laboratory testbed of an industrial wafer scanner.

A controller design is presented for directly shaping the sensitivity function in the feedback control of dual-input single-output (DISO) systems. We provide special forms of discrete-time Youla-Kucera (YK) parameterization to obtain stabilizing controllers for DISO systems, and discuss concepts to achieve a reduced-complexity formulation. The proposed YK parameterization is based on an inverse of the loop transfer function, which gives benefits such as clearer design intuition and reduced complexity in construction. The algorithm is verified by simulations and experiments on hard disk drive systems, with application to wideband vibration and harmonic disturbance rejections.

The importance of safe and flexible disturbance rejection at high frequencies has been ever increasing in modem control systems. For example, new applications of hard disk drives (HDD) require that the HDD control system be robust to (e.g., have the ability to reject, attenuate) vibration disturbances that can occur at, for example, 5000 HZ and 6000 HZ, which capability has, thus far, been unattainable. Theoretical limi tations prevent conventional disturbance observer schemes from being applied to environments is susceptible to ultra-high (e.g., 4000 HZ and above) frequency disturbance environments. This invention addresses the challenge and provide methods for accurately controlling hard disk drives to function in presence of ultra-high frequency disturbances.

The importance of safe and flexible disturbance rejection at high frequencies has been ever increasing in modem control systems. For example, new applications of hard disk drives (HDD) require that the HDD control system be robust to (e.g., have the ability to reject, attenuate) vibration disturbances that can occur at, for example, 5000 HZ and 6000 HZ, which capability has, thus far, been unattainable. Theoretical limi tations prevent conventional disturbance observer schemes from being applied to environments is susceptible to ultra-high (e.g., 4000 HZ and above) frequency disturbance environments. This invention addresses the challenge and provide methods for accurately controlling hard disk drives to function in presence of ultra-high frequency disturbances.

Variable-gear-ratio steering is an advanced feature in automotive vehicles. As the name suggest, it changes the steering gear ratio depending on the speed of the vehicle. This feature can simplify steering for the driver, which leads to various advantages, such as improved vehicle comfort, stability, and safety. One serious problem, however, is that the variable-gear-ratio system generates unnatural torque to the driver whenever the variable-gear-ratio control is activated. Such unnatural torque includes both low-frequency and steering-speed-dependent components. This paper proposes a control method to cancel this unnatural torque. We address the problem by using a tire sensor and a set of feedback and feedforward algorithms. Effectiveness of the proposed method is experimentally verified using a hardware-in-the-loop experimental setup. Stability and robustness under model uncertainties are evaluated.

This paper presents an adaptive control scheme for identifying and rejecting unknown and/or time-varying narrow-band vibrations. We discuss an idea of selective model inversion (SMI) for a (possibly nonminimum phase) plant dynamics at multiple narrow frequency regions, so that vibrations can be estimated and canceled by feedback. By taking advantage of the structure of the disturbance model, we can reduce the adaptation to identify the minimum amount of parameters, achieve accurate parameter estimation under noisy environments, and flexibly reject the narrow-band disturbances with clear tuning intuitions. Evaluation of the proposed algorithm is performed via simulation and experiments on a benchmark system for active vibration control.

A loop-shaping idea for dual-input-single-output (DISO) systems is presented in this paper. We explore special forms of Youla parameterization for obtaining stabilizing controllers for DISO systems, and discuss concepts to achieve reduced-complexity formulations with clearer design intuitions. The algorithm is verified by a benchmark control problem of dual-stage hard disk drive systems, using real-system models and actual vibration data.

We have many servo systems that require nano/micro level positioning accuracy. This requirement sets a number of interesting challenges from the viewpoint of sensing, actuation, and control algorithms. This paper considers the control aspect for precision positioning. In motion control systems at nano/micro levels, it has been noted that the control algorithm should be customized as much as possible to the spectrum of disturbances. We will examine how prior knowledge about the disturbance spectrum should be utilized in the design of control algorithms and what are advantages of such prior knowledge. The algorithms will be evaluated on a simulated hard disk drive (HDD) benchmark problem and a laboratory setup for a wafer scanner that is equipped with a laser interferometer for position measurement.

In motion-control problems such as vibration rejection, periodical reference tracking, and harmonic disturbance cancellation, the disturbances/references share a common characteristic of exhibiting concentrated energies at multiple bands of frequencies. In this paper, we discuss a feedback loop-shaping approach to address such a class of control problem. An integration of (inverse) system models is proposed to bring enhanced high-gain control at the required local frequency regions. We show that such servo enhancement can be effectively achieved if good model information is available at the disturbance frequencies, and that a rich class of design tools can be integrated for the controller formulation. The proposed algorithm is verified in simulation and experiments on vibration rejection in hard disk drives and an electrical power steering system in automotive vehicles.

This paper presents an adaptive control scheme for identifying and rejecting unknown and/or time-varying narrow-band vibrations. We discuss an idea of safely and adaptively inverting a (possibly non-minimum phase) plant dynamics at selected frequency regions, so that structured disturbances (especially vibrations) can be estimated and canceled from the control perspective. By taking advantage of the disturbance model in the design of special infinite-impulse-response (IIR) filters, we can reduce the adaptation to identify the minimum amount of parameters, achieve accurate parameter estimation under noisy environments, and flexibly reject the narrow-band disturbances with clear tuning intuitions. Evaluation of the algorithm is performed via simulation and experiments on an active-suspension benchmark.

Many servo systems are subjected to narrow-band disturbances that generate vibrations at multiple frequencies. One example is the track-following control in a hard disk drive (HDD) system, where the airflow-excited disk and actuator vibrations introduce strong and uncertain spectral peaks to the position error signal. Such narrow-band vibrations differ in each product and can appear at frequencies above the bandwidth of the control system. We present a feedback control scheme that adaptively enhances the servo performance at multiple unknown frequencies, while maintaining the baseline servo loop shape. A minimum parameter model of the disturbance is first introduced, followed by the construction of a novel adaptive multiple narrow-band disturbance observer for selective disturbance cancellation. Evaluation of the proposed algorithm is performed on a simulated HDD benchmark problem.