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Control Methodologies for Precision Positioning Systems
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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.
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... It is worth noting that in the field of high precision motion control, the concept of disturbance observer (DOB)-based control with internal model principle has been recently explored to reject disturbances with unknown and/or time-varying spectra [7]. For example, a DOB-based algorithm has been formulated and implemented to a wafer-scanning process in lithography [8]. The fundamental idea of DOB control is to conduct an internal disturbance observation using model inversion and then to achieve disturbance cancelation by using an inner feedback control loop. ...
... Recall Eqs. (7) and (8). Based on the internal model principle [13], to asymptotically reject the disturbance, the following equation should be satisfied: ...
... where b 2 ð0; 1Þ. The design of B p ðbz À1 Þ is based on the damped pole-zero pair principle [7,8], which entertains the advantage of controlled waterbed effect in loop shaping. ...
Time-varying unknown wind disturbances influence significantly the dynamics of wind turbines. In this research, we formulate a disturbance observer (DOB) structure that is added to a proportional-integral-derivative (PID) feedback controller, aiming at asymptotically rejecting disturbances to wind turbines at above-rated wind speeds. Specifically, our objective is to maintain a constant output power and achieve better generator speed regulation when a wind turbine is operated under time-varying and turbulent wind conditions. The fundamental idea of DOB control is to conduct internal model-based observation and cancelation of disturbances directly using an inner feedback control loop. While the outer-loop PID controller provides the basic capability of suppressing disturbance effects with guaranteed stability, the inner-loop disturbance observer is designed to yield further disturbance rejection in the low frequency region. The DOB controller can be built as an on-off loop, that is, independent of the original control loop, which makes it easy to be implemented and validated in existing wind turbines. The proposed algorithm is applied to both linearized and nonlinear National Renewable Energy Laboratory (NREL) offshore 5-MW baseline wind turbine models. In order to deal with the mismatch between the linearized model and the nonlinear turbine, an extra compensator is proposed to enhance the robustness of augmented controller. The application of the augmented DOB pitch controller demonstrates enhanced power and speed regulations in the above-rated region for both linearized and nonlinear plant models.
... Yet, as the attenuation width is increased further, the amplification of intermediate frequencies due to the waterbed effect also increases [23]. Additional design considerations are therefore necessary for achieving better performance, such as the gain scheduling and the use of a damped notch filter [24]. ...
... In the proposed quasi RC, N is designed to be an integer by shifting the fundamental frequency to the least common multiple (LCM) between itself and the sampling frequency, that is, N = f s /LCM f s , f 0 . The stability conditions for the wide-band and quasi RCs are the same as those for the plug-in RC design in [24], that is,P −1 z −1 , Q z −1 , and C z −1 belong to the set of stable, proper, and rational transfer functions. ...
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.
... DOB is a robust control technique to reject disturbances with guaranteed robust stability for linear system [18]. Moreover, given a stabilizing nominal controller, Q-filter in DOB can be an arbitrary stable filter to make the sensitivity function shaped as desired [19]. It has been applied to robust lateral trajectory tracking and its effectiveness has been verified by experiments [20]. ...
... We design Q as a second-order low-pass filter to reject lowfrequency disturbances, because κ s,ref should have relatively low frequency components for smooth reference trajectory. When modeling errors exist, we can use the robust control theorem to ensure robust stability [19]. However, modeling uncertainty between the linear model and the nonlinear model nonlinear model is involved in our problem, which complicates the analysis. ...
Although deep reinforcement learning (deep RL) methods have lots of strengths that are favorable if applied to autonomous driving, real deep RL applications in autonomous driving have been slowed down by the modeling gap between the source (training) domain and the target (deployment) domain. Unlike current policy transfer approaches, which generally limit to the usage of uninterpretable neural network representations as the transferred features, we propose to transfer concrete kinematic quantities in autonomous driving. The proposed robust-control-based (RC) generic transfer architecture, which we call RL-RC, incorporates a transferable hierarchical RL trajectory planner and a robust tracking controller based on disturbance observer (DOB). The deep RL policies trained with known nominal dynamics model are transfered directly to the target domain, DOB-based robust tracking control is applied to tackle the modeling gap including the vehicle dynamics errors and the external disturbances such as side forces. We provide simulations validating the capability of the proposed method to achieve zero-shot transfer across multiple driving scenarios such as lane keeping, lane changing and obstacle avoidance.
... Disturbance observers usually update the control input via feedback compensation [5]- [7]. Youla parameterization can be parameterized either as an add-on compensation at the plant input side [8], [9], or a combined compensation at the plant input and controller input [10], [11]. In feedforwardrelated control, iterative learning control (ILC) [12]- [16] and adaptive or sensor-based feedforward compensation [17]- [19] can be configuraed as add-on algorithms either at the plant input or at the reference input. ...
... and Y (s, e i ) are, respectively, the Laplace transforms of the natural transient and the transient due to input discontinuity. Using (9) gives ...
... Inheriting from the plug-in RC design, the stability conditions for the wide-band and quasi RCs are:̂− 1 ( ), ( ), and ( ) belong to the set of stable, proper, and rational transfer functions (Chen & Tomizuka, 2013). ...
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.
... These error sources are difficult, or infeasible, to eliminate completely by better mechanical designs. For instance, the interference between the galvo mirrors is intrinsic to the beam-steering mechanism; and vibrations in a complex mechanical system is unavoidable [2][3][4]. ...
Selective laser sintering (SLS) is an additive manufacturing (AM) process that builds 3-dimensional (3D) parts by scanning 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 urging 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 always 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.
... Either for general low-frequency enhancement [5]- [7], or for the extensions to structured disturbance rejection [8]- [10], disturbance observers usually update the commands at the input side of the plant. Youla parameterization can be parameterized either as an add-on compensation at the plant input side [11], [12], or a combined compensation at the plant input and controller input [13], [14]. In feedforward-related control, adaptive or sensorbased feedforward compensation [15]- [17] can be configured Tianyu Jiang (email: tianyu.jiang@uconn.edu) ...
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.
Chatter vibrations are a type of self-exited vibrations observed in many subtractive manufacturing processes. They limit achievable material remove rate (MRR), reduce tool life, resulting in poor surface finish, and even damage the manufacturing equipment. This article proposes a novel control system design for machine tool feed drives, which modulates cutting tool motion based on the in-process vibration measurements to mitigate chatter vibrations. The proposed approach has two key contributions. First, as opposed to introducing modal damping to the structure, the proposed approach stabilizes machining process dynamics by controlling its governing delay differential equation. H∞ control framework is used to design the controller and ensures robust process stability. The controller design problem is postulated as a convex optimization problem with linear matrix inequalities, which is solved to global optimality. Second, the proposed controller is implemented as an add-on compensator that works jointly with an existing servo motion control system to realize both positioning and chatter vibration control. Experimental validations are conducted on a lathe equipped with a fast tool servo actuator. It is shown that regenerative chatter vibrations in the orthogonal turning process can be suppressed robustly and up to five times increase in MRR (productivity) can be achieved.
The neural network policies are widely explored in the autonomous driving field, thanks to their capability of handling complicated driving tasks. However, the practical deployment of such policies is slowed down due to their lack of robustness against modeling gap and external disturbances. In our prior work, we proposed a planner-controller architecture and applied a disturbance-observer-based (DOB) robust tracking controller to reject the disturbances and achieved zero-shot policy transfer. In this paper, we present our latest progress on improving the policy transfer performance under this framework. Concretely, we applied adaptive DOB, so as to more accurately model the inverse system dynamics and increase the cut-off frequency of the Q-filter in the DOB. A closed-loop reference path smoothing algorithm is introduced to alleviate the step disturbance input imposed by the reference trajectory re-planning. On the neural network control policy side, we applied the parallel attribute networks, a hierarchical modular policy network to dynamically handle various driving tasks. We have carried out various simulations and experiments to validate the capability of our proposed method to achieve sim-to-sim and sim-to-real policy transfer. The proposed method achieves the most outstanding performance among a series of baseline control schemes.
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.
The disturbance observer (DOB) has been one effective robust control approach for servo enhancement in single-input-single-output systems. This paper presents a new extension of the DOB idea to dual-input-single-output systems, and discusses an optimal Q-filter design. The proposed decoupled disturbance observer (DDOB) provides a flexible approach to use the most suitable actuators for compensating disturbances at different frequencies. Such a scheme is helpful, e.g., for modern dual-stage hard disk drives, where enhanced servo design is becoming more and more essential in the presence of audio vibrations.
In this paper, an adaptive control scheme is developed to reject unknown multiple narrow-band disturbances in a hard disk drive. An adaptive notch filter is developed to efficiently estimate the frequencies of the disturbance. Based on the correctly estimated parameters, a disturbance observer with a newly designed multiple band-pass filter is constructed to achieve asymptotic perfect rejection of the disturbance. Evaluation of the control scheme is performed on a benchmark problem for HDD track following.
Repetitive control is formulated and analyzed in the discrete-time domain. Sufficiency conditions for the asymptotic convergence of a class of repetitive controllers are given. The “plug-in” repetitive controller is introduced and applied to track-following in a disk-file actuator system. Inter-sample ripples in the tracking error were present when the “plug-in” repetitive controller was installed. The performance is enhanced, however, when the zero-holding device is followed by a low- pass filter or replaced by a delayed first-order hold.
In any system, if there exists a linear relationship between two variables, then it is said that it is a linear system.
The hard disk drive is one of the finest examples of the precision control of mechatronics, with tolerances less than one micrometer achieved while operating at high speed. Increasing demand for higher data density as well as disturbance-prone operating environments continue to test designers’ mettle. Explore the challenges presented by modern hard disk drives and learn how to overcome them with Hard Disk Drive: Mechatronics and Control. Beginning with an overview of hard disk drive history, components, operating principles, and industry trends, the authors thoroughly examine the design and manufacturing challenges. They start with the head positioning servomechanism followed by the design of the actuator servo controller, the critical aspects of spindle motor control, and finally, the servo track writer, a critical technology in hard disk drive manufacturing. By comparing various design approaches for both single- and dual-stage servomechanisms, the book shows the relative pros and cons of each approach. Numerous examples and figures clarify and illustrate the discussion. Exploring practical issues such as models for plants, noise reduction, disturbances, and common problems with spindle motors, Hard Disk Drive: Mechatronics and Control avoids heavy theory in favor of providing hands-on insight into real issues facing designers every day.
A self-contained introduction to adaptive inverse control Now featuring a revised preface that emphasizes the coverage of both control systems and signal processing, this reissued edition of Adaptive Inverse Control takes a novel approach that is not available in any other book. Written by two pioneers in the field, Adaptive Inverse Control presents methods of adaptive signal processing that are borrowed from the field of digital signal processing to solve problems in dynamic systems control. This unique approach allows engineers in both fields to share tools and techniques. Clearly and intuitively written, Adaptive Inverse Control illuminates theory with an emphasis on practical applications and commonsense understanding. It covers: the adaptive inverse control concept; Weiner filters; adaptive LMS filters; adaptive modeling; inverse plant modeling; adaptive inverse control; other configurations for adaptive inverse control; plant disturbance canceling; system integration; Multiple-Input Multiple-Output (MIMO) adaptive inverse control systems; nonlinear adaptive inverse control systems; and more. Complete with a glossary, an index, and chapter summaries that consolidate the information presented, Adaptive Inverse Control is appropriate as a textbook for advanced undergraduate- and graduate-level courses on adaptive control and also serves as a valuable resource for practitioners in the fields of control systems and signal processing. © 2008 the Institute of Electrical and Electronic Engineers. All rights reserved.
