Linear Hall sensors are a cost-effective alternative to optical encoders for measuring the rotor positions of actuators, with the main challenge being that they exhibit position-dependent inaccuracies resulting from manufacturing tolerances. This paper develops a data-driven calibration procedure for linear analog Hall sensors that enables accurate online estimates of the rotor angle without requiring expensive external encoders. The approach combines closed-loop data collection with nonlinear identification to obtain an accurate model of the sensor inaccuracies, which is subsequently used for online compensation. Simulation results show that when the flux density model structure is known, measurement errors are reduced to the sensor noise floor, and experiments on an industrial setup demonstrate a factor of 2.6 reduction in the root-mean-square measurement error. These results confirm that Hall sensor inaccuracies can be calibrated even when no external encoder is available, improving their practical applicability.

Piezo-stepper actuators enable accurate positioning through the sequential contraction and expansion of piezoelectric elements, generating a walking motion. The aim of this paper is to reduce velocity ripples caused by parasitic effects, due to hysteresis in the piezoelectric material and mechanical misalignments, through suitable feedforward control. The presented approach involves the integration of a rate-dependent hysteresis model with a position-dependent feedforward learning scheme to compensate for these effects. Experimental results show that this approach leads to a significant reduction in the velocity ripples, even when the target velocity is changed. These results enable the use of piezo-stepper actuators in applications requiring high positioning accuracy and stiffness over a long stroke, without requiring expensive position sensors for high-gain feedback.

Frequency Response Function (FRF) measurements are widely used in gravitational wave detectors, e.g., for the design of controllers, calibrating signals, and diagnosing problems with system dynamics. The aim of this paper is to present GraFIT: a toolbox that enables fast, inexpensive, and accurate identification of FRF measurements for gravitational wave detectors compared to the commonly used approaches, including common spectral analysis techniques. The toolbox builds upon recent developments in non-parametric system identification by utilizing a local modeling technique, which is particularly effective in reducing the impact of transient effects. It is furthermore designed to be user-friendly, handling systems of arbitrary input-output dimensions, and systems operating in a closed loop. The toolbox is validated on two experimental case studies of the Virgo detector, illustrating more than a factor 3 reduction in the estimated standard deviation using GraFIT for the same measurement times and comparable estimated standard deviations with up to ten times less data using GraFIT with respect to the commonly used spectral analysis method. As a result, GraFIT can reduce commissioning time and detector downtime due to noise injections, while also improving the overall quality of the measurements.

Increasingly stringent performance requirements for motion systems necessitate explicit control of the flexible dynamic behavior. The aim of this paper is to present an approach to identify spatio-temporal models of overactuated mechatronic systems with a limited number of spatially distributed sensors. The proposed approach exploits the modal modeling framework and exploits the symmetry in modal models to enhance the spatial resolution of the identified spatially-sampled modal models. Spatio-temporal models are identified by updating prior finite element method-based models based on the identified extended modal models. The experimental results illustrate the effectiveness of the proposed approach for the identification of complex position-dependent mechanical systems.

This paper presents a framework for the derivation of a noise budget and the subsequent utilization in the optimization of the control design, using the laser frequency stabilization loop in the Virgo interferometer, which is a complex nested feedback system, as an experimental case study. First, the system dynamics and noise sources are modeled and experimentally verified to produce the noise budget, after which an optimization problem using the H2 norm is formulated and tailored to the specific design requirements for the detector. The structure of the synthesized controller is then used to produce an improved control design. Experimental verification of the developed controller on the Virgo interferometer shows roughly a factor 3 reduction in root-mean-square error, illustrating the effectiveness of the presented method.

Some of the feedback loops in the Advanced Virgo+ Gravitational Wave detector exhibit strong coupling and this coupling also varies over time. This paper presents a method to decouple the loops using a decoupling matrix, removing restrictions on the attainable performance of the feedback loops. The presented method performs batch-wise identification of the coupling matrix using only a single sinusoid per loop as perturbation by exploiting the specific structure of the plant to interpolate between frequency bins. The presented method is implemented on AdV+ and is shown to lead to significant decoupling of the loops and to keep the interaction terms low over time.

Switched Reluctance Motors (SRMs) are widely used for their simplicity and cost-effectiveness, for example, in coarse laser pointing for free-space optical (FSO) communication, with torque ripple being a challenge in their implementation. This paper introduces an automated, modelfree approach to minimize torque ripple in SRMs despite manufacturing variations. Using an extremum-seeking approach, the commutation parameters are adapted online to mitigate the position-dependent velocity ripple through gradient descent. Simulations show that the method's effectiveness is consistent across different SRMs, rendering it applicable to mass production, and experimental results verify that torque ripple is almost entirely eliminated in several hours. The developed approach enables accurate SRM control with minimal expert knowledge, functioning as a crucial step toward their deployment in constellation projects for FSO communication.

Switched Reluctance Motors (SRMs) are cost-effective electric actuators that utilize magnetic reluctance to generate torque, with torque ripple arising from unaccounted manufacturing defects in the rotor tooth geometry. This paper aims to design a versatile, resource-efficient commutation function for accurate control of a range of SRMs, mitigating torque ripple despite manufacturing variations across SRMs and individual rotor teeth. The developed commutation function optimally distributes current between coils by leveraging the variance in the torque-current-angle model and is designed with few parameters for easy integration on affordable hardware. Monte Carlo simulations and experimental results show a tracking error reduction of up to 31% and 11%, respectively. The developed approach is beneficial for applications using a single driver for multiple systems and those constrained by memory or modeling effort, providing an economical solution for improved tracking performance and reduced acoustic noise.

Actuators that require commutation algorithms, such as the switched reluctance motor (SRM) considered in this paper and employed in the coarse pointing assembly (CPA) for free-space optical communication, often have torque-ripple disturbances that are periodic in the commutation-angle domain that deteriorate the positioning performance. The aim of this paper is to model the torque ripple as a Gaussian Process (GP) in the commutation-angle domain and consequently compensate for it at arbitrary velocity. The approach employs repetitive control (RC) at a constant velocity. A spatial GP with a periodic kernel is trained using data that is obtained from the RC step resulting in a static non-linear function for compensation at arbitrary velocity. Stability conditions are provided for both steps. The approach is successfully applied to a CPA prototype to improve the tracking performance for laser communication, where the torque ripple is compensated at arbitrary velocity.

Next-generation deformable mirrors are envisaged to exhibit low-frequency flexible dynamics and to contain a large number of spatially distributed actuators due to increasingly stringent performance requirements. The increasingly complex system characteristics necessitate identifying the flexible dynamic behavior for design validation and next-generation control. The aim of this paper is to develop a unified approach for the identification of mechanical systems with a large number of spatially distributed actuators and a limited number of sensors. A frequency domain-based approach using local modeling techniques is developed. The modal modeling framework is employed to analyze the design and create outputs that were not measured. The proposed approach is applied to an experimental deformable mirror case study that illustrates the effectiveness of the proposed approach.

Gravitational Wave detectors require low-noise sensors combined with high-performance feedback loops to maximize the detector sensitivity in the low-frequency detection range. Some feedback loops in the detector are strongly coupled and their coupling varies over time, which is inherent to the optical configuration and the optical readout scheme used to obtain error signals for the feedback loops. This paper presents a control-based approach to deal with the time-varying interaction among three of the longitudinal degrees of freedom in the Advanced Virgo Plus detector, using the pre-existing infrastructure of the detector. An intuitive Multiple-Input Multiple-Output stability criterion is presented that illustrates how the time-varying coupling affects the stability of the feedback loops, as well as a method that identifies the coupling online and updates a decoupling matrix accordingly. Experiment results of the proposed method on the Advanced Virgo Plus detector illustrate continuous minimization of the coupling over time. Using the derived stability criterion, it is furthermore shown that the coupling is sufficiently minimized such that the interaction terms can be neglected in the control design, resulting in an improved controller performance.

Flexible dynamics in motion systems lead to inherent spatio-temporal system behavior. The aim of this paper is to develop an unified approach for the identification of modal models of spatio-temporal overactuated systems. The approach exploits the modal modeling framework and the overactuated setting to enhance the estimation of the spatial system behavior. The proposed approach is applied in an experimental case study. The case study considers an experimental overactuated stage and illustrates the effectiveness of the proposed approach.

Switched Reluctance Motors (SRMs) enable power-efficient actuation with mechanically simple designs. This paper aims to identify the nonlinear relationship between torque, rotor angle, and currents, to design commutation functions that minimize torque ripple in SRMs. This is achieved by conducting specific closed-loop experiments using purposely imperfect commutation functions and identifying the nonlinear dynamics via Bayesian estimation. A simulation example shows that the presented method is robust to position-dependent disturbances, and experiments suggest that the identification method enables the design of commutation functions that significantly increase performance. The developed approach enables accurate identification of the torque-current-angle relationship in SRMs, without the need for torque sensors, an accurate linear model, or an accurate model of position-dependent disturbances, making it easy to implement in production.

Data-driven feedforward control for tracking of varying and non-resetting point-to-point references requires continuous updating of feedforward parameters instead of task-by-task updating. The aim of this paper is to develop an adaptive feedforward controller for non-resetting point-to-point motion tasks by a data-driven feedforward controller. An approximate optimal instrumental variable (IV) estimator with real-time bootstrapping is employed in a closed-loop setting to update the feedforward parameters. A case study on a wafer-stage and experimental validation on a benchmark motion system show the performance benefit.

Repetitive control (RC) can perfectly attenuate disturbances that are periodic in the time domain. The aim of this article is to develop an RC approach that compensates for disturbances that are time-domain nonperiodic but are repeating in the position domain. The developed position-domain buffer consists of a Gaussian process (GP), which is learned using appropriate dynamic filters and nonequidistant data. This approach estimates position-domain disturbances resulting in perfect compensation. The method is successfully applied to a substrate carrier system, demonstrating performance robustness against time-domain nonperiodic disturbances that are amplified by traditional RC.

Dynamic error budgets are an essential tool in identifying opportunities for improvements in a control system for Gravitational Wave detectors, but their potential is often not fully utilized in the control design. This paper presents a model and dynamic error budget for a challenging nested control system in the Advanced Virgo detector in combination with a systematic control design framework for one of the controllers. This framework fully utilizes the dynamic error budget by using H₂ synthesis to allow for fast iterations in the control design when dealing with conflicting control objectives. Simulations together with experimental results on Advanced Virgo illustrate the effectiveness of the presented framework.

Sensors in high-precision mechatronic systems require accurate calibration, which is achieved using test beds that, in turn, require even more accurate calibration. The aim of this paper is to develop a cascaded calibration method for position sensors of mechatronic systems while taking into account the variance of the calibration model of the test bed. The developed calibration method employs Gaussian Process regression to obtain a model of the position-dependent sensor inaccuracies by combining prior knowledge of the sensor with data using Bayesian inference. Monte Carlo simulations show that the developed calibration approach leads to significantly higher calibration accuracy when compared to alternative regression techniques, especially when the number of available calibration points is limited. The results indicate that more accurate calibration of position sensors is possible with fewer resources.

Repetitive control enables the exact compensation of periodic disturbances if the internal model is appropriately selected. The aim of this paper is to develop a novel synthesis technique for repetitive control (RC) based on a new more general internal model. By employing a Gaussian process internal model, asymptotic rejection is obtained for a wide range of disturbances through an appropriate selection of a kernel. The implementation is a simple linear time-invariant (LTI) filter that is automatically synthesized through this kernel. The result is a user-friendly design approach based on a limited number of intuitive design variables, such as smoothness and periodicity. The approach naturally extends to reject multi-period and non-periodic disturbances, exiting approaches are recovered as special cases, and a case study shows that it outperforms traditional RC in both convergence speed and steady-state error.

Gravitational Wave detectors require feedback control to control the length between the sensitive components of the detector. The degrees of freedom in the control system are inherently coupled and the level of interaction furthermore varies over time. A systematic control design approach for the feedback controllers is presented which provides a guide on how to cope with the varying levels of interaction. A new controller for one of the loops has been designed and experimental results measured on the Gravitational Wave detector Advanced Virgo show a significant reduction in the root mean square error of the loop with the new controller.