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.

/pdf/essentials-of-robust-control-3kaks6yk3h.pdf

Essentials of Robust Control

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.

http://promexico.me/Rubenius/WhitePapers/sdarticle%20(1).pdf

Progress in electrical energy storage system: A critical review

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.

A survey of iterative learning control

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.

/pdf/social-lstm-human-trajectory-prediction-in-crowded-spaces-wwxok9svq7.pdf

Social LSTM: Human Trajectory Prediction in Crowded Spaces

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.

/pdf/reinforcement-learning-in-robotics-a-survey-4w4397qx9i.pdf

Reinforcement learning in robotics: A survey

The dynamics of an electromechanically actuated metal V-belt (Empact) CVT is analyzed by studying a simplified linear model of the actuation system and a driveline model which includes the slip dynamics of the variator. The actuation system shows several CVT ratio depending modes. Linearization of the slip dynamics shows that the location and, moreover, the damping of the modes depends significantly on the amount of slip in the variator. Using pole-zero locations of the system it is shown that due to high overclamping a coupling between the primary and secondary side of the variator occurs with very large damping and due to underclamping the input and output sides of the variator are decoupled with low or even negative damping, resulting in an unstable system. Furthermore non-minimum phase behavior of the actuation is described. Using identification results from a non-linear model of the Empact CVT the interaction of the actuation and driveline dynamics is analyzed. Finally, measurements on a prototype of the Empact show similar behavior, however with very large damping of all of the modes.

/pdf/dynamic-analysis-of-the-empact-cvt-ratio-and-slip-dependent-2soirn06a3.pdf

Dynamic analysis of the Empact CVT : ratio and slip dependent, non-minimum phase dynamics

Non-stationary disturbances in motion systems generally limit the closed-loop performance. If these disturbance can be measured, this measurement can be used to enable a linear parameter varying (LPV) controller to adapt itself to the current operating condition, resulting in a closed-loop system with an overall increased performance. In this paper, this idea is applied to an active vibration isolation system.

http://www.mate.tue.nl/mate/pdfs/10840.pdf

LPV control of an active vibration isolation system

A plasma boundary reconstruction method based on optical images was introduced by Hommen et al.[1]. Consistency of the boundary with the boundary from magnetic measurements was demonstrated for a few cases, but systematic validation over a wide range of plasma parameters was lacking. Here we present a systematic comparison of the EFIT (magnetic) and OFIT (optical) boundaries for more than two hundred MAST (Mega Ampere Spherical Tokamak) discharges. For this comparison, the OFIT concept had to be implemented in the MAST data analysis chain and needed to be improved on a number of points. A dimensionless figure of merit has been introduced comparing the non-overlapping regions with the overlapping regions. With this criterion, overall discrepancies of about 6-8% were found between the optical and magnetic boundary. These dimensionless discrepancies translate to overall distances between the EFIT and OFIT boundaries of about 2-3 cm. Upper-limits on the error of OFIT, of 2:7 cm for the DND case and 4:1 cm for the SND case, were found. No (strong) correlation was found with plasma parameters such as normalized pressure s or self induction li. We show that a significant part of the discrepancy is likely caused by faults in the EFIT reconstruction. This leads to the conclusion that the OFIT technique, if implemented and used correctly, is usable for reliable real-time detection of plasma position and shape, with an overall error less than 3-4 cm.

Validation of the OFIT technique for the detection of the plasma boundary at MAST : traineeship report

Our research focusses on longitudinal sheet control in a cut sheet printer paper path. The control problem is split up into a low level that encompasses motor control design for tackling local disturbances and uncertainties, and a high level that performs sheet feedback control, resulting in robustness at the sheet level. Consequently, a cascade control structure is chosen. The design of sheet controllers is considered here under the assumption of perfect low-level motor control.

M Maarten Steinbuch

Papers

Dynamic analysis of the Empact CVT : ratio and slip dependent, non-minimum phase dynamics

LPV control of an active vibration isolation system

Validation of the OFIT technique for the detection of the plasma boundary at MAST : traineeship report

Cascaded Sheet Feedback Control in a Printer Paper Path

Control-Oriented Identification of an Electromechanically Actuated Pushbelt type CVT