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M Maarten Steinbuch

Bio: M Maarten Steinbuch is an academic researcher from Eindhoven University of Technology. The author has contributed to research in topics: Control theory & Feed forward. The author has an hindex of 51, co-authored 630 publications receiving 11892 citations. Previous affiliations of M Maarten Steinbuch include Nanyang Technological University & Delft University of Technology.


Papers
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Journal ArticleDOI
TL;DR: In this paper, a measurement machine for the European Extremely Large Telescope (E-ELT) is presented based on a non-contact single-point scanning technique, capable of measuring with nanometre accuracy, being universal, fast and with low operational costs.
Abstract: To enable important scientific discoveries, ESO has defined a new ground-based telescope: the European Extremely Large Telescope (E-ELT). The baseline design features a telescope with a 39-m-class primary mirror (M1), making it the largest and most powerful telescope in the world. The M1 consists of 798 hexagonal segments, each about 1.4 m wide, but only 50 mm thick. In the last stages of the manufacturing process of these M1 segments, a nanometre-accurate metrology method is required for the M1 to be within specifications. The segments have to be measured on their whiffle-tree support structures with a nanometre-level uncertainty, with a total budget on form accuracy of 50 nm RMS for any segment assembly. In this paper a measurement machine design is presented based on a non-contact single-point scanning technique, capable of measuring with nanometre accuracy, being universal, fast and with low operational costs, providing suitable metrology for M1 segments. A tactile precision probe is implemented to be able to use the machine in earlier stages of the segment manufacturing process. In particular, this paper describes the design of the air-bearing motion system and the separate metrology system based on a moving Sintered Silicon Carbide tube, a fixed Zerodur metrology frame and an interferometric system for a direct and short metrology loop. Preliminary calculations show nanometre-level measurement uncertainty after calibration.

8 citations

Proceedings ArticleDOI
01 Dec 2011
TL;DR: In this article, an approach to estimate the maximum friction between the pushbelt and pulley set in a mass-produced Continuously Variable Transmission (CVT) is described, which is useful to accurately determine the maximum transmittable torque and to monitor the variator condition.
Abstract: This study describes an approach to estimate the maximum friction between the pushbelt and pulley set in a mass-produced Continuously Variable Transmission. Up-to-date friction knowledge is useful to accurately determine the maximum transmittable torque and to monitor the variator condition. Besides standard sensors, torque signals are assumed to be available. An adaptive estimator is presented based on the Kalman filter, which estimates friction-related parameters to find the maximum friction. The filter requires no a priori knowledge of the maximum friction and needs no detailed friction model. Experiments show that this method can be used for both an undamaged and damaged pushbelt.

8 citations

Proceedings ArticleDOI
18 Aug 2011
TL;DR: In this paper, a method of objectively analyzing the performance index for the optimal control problem of a parallel hybrid electric vehicle is introduced by using the Singular Value Decomposition method.
Abstract: The definition of a performance index for the optimization design and optimal control problem of a Hybrid Electric Vehicle is not often considered and analyzed explicitly. In literature, there is no study about proposing a method of building or evaluating whether a performance index is appropriate. In this paper a method of objectively analyzing the performance index for the optimal control problem of a parallel Hybrid Electric Vehicle is introduced. The correlations and interdependencies among the objectives of the performance index are addressed by using the Singular Value Decomposition method. It is found that a simplified performance index consisting of fuel consumption and comfort can be obtained without sacrificing the vehicle performance compared to the case with the original one including fuel consumption, comfort and driveability.

8 citations

Journal ArticleDOI
TL;DR: In this article, the authors used a state-of-the-art damper for high-precision motion stages as a sliding plate rheometer for measuring linear viscoelastic properties in the frequency range of 10 Hz-10 kHz.
Abstract: This paper presents the use of a state of the art damper for high-precision motion stages as a sliding plate rheometer for measuring linear viscoelastic properties in the frequency range of 10 Hz–10 kHz. This device is relatively cheap and enables to obtain linear viscoelastic (LVE) fluid models for practical use in precision mechanics applications. This is an example of reversed engineering, i.e., turning a machine part into a material characterization device. Results are shown for a high-viscosity fluid. The first part of this paper describes the damper design that is based on a high-viscosity fluid. This design is flexure-based to minimize parasitic nonlinear forces such as hysteresis and stick-slip. In the second part of the paper, LVE fluid characterization by means of the damper setup is presented. Measurements are performed and model parameters are fitted by a non-convex optimization algorithm in order to obtain the frequency-dependent behavior of the fluid. The resulting fluid model is validated by comparison with a second measurement with a different damper geometry. This paper shows that LVE fluid characterization between 10 Hz and 10 kHz for elastic high-viscosity fluids is possible with a motion stage damper for which the undamped behavior is known.

8 citations

Journal ArticleDOI
TL;DR: In this article, the authors present an overview of mechanical-hybrid vehicle concepts found in the literature, and compare the fuel saving potential and the estimated cost of a selection of four competitive powertrain topologies.

8 citations


Cited by
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Book
05 Oct 1997
TL;DR: In this article, the authors introduce linear algebraic Riccati Equations and linear systems with Ha spaces and balance model reduction, and Ha Loop Shaping, and Controller Reduction.
Abstract: 1. Introduction. 2. Linear Algebra. 3. Linear Systems. 4. H2 and Ha Spaces. 5. Internal Stability. 6. Performance Specifications and Limitations. 7. Balanced Model Reduction. 8. Uncertainty and Robustness. 9. Linear Fractional Transformation. 10. m and m- Synthesis. 11. Controller Parameterization. 12. Algebraic Riccati Equations. 13. H2 Optimal Control. 14. Ha Control. 15. Controller Reduction. 16. Ha Loop Shaping. 17. Gap Metric and ...u- Gap Metric. 18. Miscellaneous Topics. Bibliography. Index.

3,471 citations

Journal ArticleDOI
TL;DR: In this paper, a review of electrical energy storage technologies for stationary applications is presented, with particular attention paid to pumped hydroelectric storage, compressed air energy storage, battery, flow battery, fuel cell, solar fuel, superconducting magnetic energy storage and thermal energy storage.
Abstract: Electrical energy storage technologies for stationary applications are reviewed. Particular attention is paid to pumped hydroelectric storage, compressed air energy storage, battery, flow battery, fuel cell, solar fuel, superconducting magnetic energy storage, flywheel, capacitor/supercapacitor, and thermal energy storage. Comparison is made among these technologies in terms of technical characteristics, applications and deployment status.

3,031 citations

Journal ArticleDOI
TL;DR: Though beginning its third decade of active research, the field of ILC shows no sign of slowing down and includes many results and learning algorithms beyond the scope of this survey.
Abstract: This article surveyed the major results in iterative learning control (ILC) analysis and design over the past two decades. Problems in stability, performance, learning transient behavior, and robustness were discussed along with four design techniques that have emerged as among the most popular. The content of this survey was selected to provide the reader with a broad perspective of the important ideas, potential, and limitations of ILC. Indeed, the maturing field of ILC includes many results and learning algorithms beyond the scope of this survey. Though beginning its third decade of active research, the field of ILC shows no sign of slowing down.

2,645 citations

Proceedings ArticleDOI
27 Jun 2016
TL;DR: This work proposes an LSTM model which can learn general human movement and predict their future trajectories and outperforms state-of-the-art methods on some of these datasets.
Abstract: Pedestrians follow different trajectories to avoid obstacles and accommodate fellow pedestrians. Any autonomous vehicle navigating such a scene should be able to foresee the future positions of pedestrians and accordingly adjust its path to avoid collisions. This problem of trajectory prediction can be viewed as a sequence generation task, where we are interested in predicting the future trajectory of people based on their past positions. Following the recent success of Recurrent Neural Network (RNN) models for sequence prediction tasks, we propose an LSTM model which can learn general human movement and predict their future trajectories. This is in contrast to traditional approaches which use hand-crafted functions such as Social forces. We demonstrate the performance of our method on several public datasets. Our model outperforms state-of-the-art methods on some of these datasets. We also analyze the trajectories predicted by our model to demonstrate the motion behaviour learned by our model.

2,587 citations

Journal ArticleDOI
TL;DR: This article attempts to strengthen the links between the two research communities by providing a survey of work in reinforcement learning for behavior generation in robots by highlighting both key challenges in robot reinforcement learning as well as notable successes.
Abstract: Reinforcement learning offers to robotics a framework and set of tools for the design of sophisticated and hard-to-engineer behaviors. Conversely, the challenges of robotic problems provide both inspiration, impact, and validation for developments in reinforcement learning. The relationship between disciplines has sufficient promise to be likened to that between physics and mathematics. In this article, we attempt to strengthen the links between the two research communities by providing a survey of work in reinforcement learning for behavior generation in robots. We highlight both key challenges in robot reinforcement learning as well as notable successes. We discuss how contributions tamed the complexity of the domain and study the role of algorithms, representations, and prior knowledge in achieving these successes. As a result, a particular focus of our paper lies on the choice between model-based and model-free as well as between value-function-based and policy-search methods. By analyzing a simple problem in some detail we demonstrate how reinforcement learning approaches may be profitably applied, and we note throughout open questions and the tremendous potential for future research.

2,391 citations