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

In this paper, a method is presented to estimate the motion of a vehicle occupant in frontal impact. Knowledge of the occupant's motion during a crash can significantly reduce the risk of injury, as restraint systems could be real-time adapted to the optimal settings. It is shown that the chest acceleration of the occupant, an important measure of injury, is accurately estimated by filtering of the belt displacement at the retractor side. Low order, nonlinear models are constructed from complex models, and a state estimator filter is designed using a linearization of these low order models.

/pdf/state-estimator-design-for-real-time-controlled-restraint-1u3wll18mh.pdf

State Estimator Design for Real-time Controlled Restraint Systems

With disturbance feedforward compensation (DFC), input disturbances are measured and compensated to cancel the effect of the disturbance. Perfect cancellation is not possible in practice due to the causal nature of DFC, in which the compensation generally comes too late. Therefore, non-perfect plant inversion, controller discretization and sensor dynamics lead to a non-zero residual error. The properties of this residual error are described in the frequency domain using a theoretical framework that is closely related to the design constraints known from filtering theory. It is shown that, like in feedback control systems, performance limitations of DFC systems are described by a waterbed effect. An experimental validation is included to demonstrate the properties of the residual error on an active hard-mounted vibration isolation setup.

Performance trade-offs in disturbance feedforward compensation of active hard-mounted vibration isolators

High order repetitive control has been introduced to overcome performance decay of repetitive control systems under varying frequency of the signals to be tracked/rejected or improving the interhamonic behavior. However, most high order repetitive internal models used to improve frequency uncertainty are unstable, as a consequence practical implementations are more difficult. In this work a stable, second order odd-harmonic repetitive control system is presented and studied. The proposed internal model has been implemented and validated in a shunt active filter current controller. This high order controller allows dealing with the grid frequency variations without using adaptive schemes.

/pdf/second-order-odd-harmonic-repetitive-control-and-its-5eclzo2ecr.pdf

Second-order odd-harmonic repetitive control and its application to active filter control

In this paper, gear shifting characteristics of vehicles equipped with an Automated Manual Transmission (AMT) and PowerShift-AMT (PS-AMT) are analyzed and compared in order to study their effects on the fuel economy. A "rapid" upshift strategy proposed for PS-AMT shows that relative fuel saving can be achieved up to 8.5% compared to the case of the AMT with prescribed gear shifting schedule over NEDC. To fully explore potential fuel savings with respect to gear shifting strategy, Dynamic Programming (DP) is utilized for PS-AMT system to derive a globally optimal shifting schedule. Simulation result reveals that relative fuel economy improvement can be reached up 10.7%. A systematic approach is proposed to study a tradeoff between fuel consumption and driveability with respect to gear shifting strategy. The optimization problem of which the cost function consists of fuel consumption, power reserve and shifting cost is formulated and solved for optimal gear shifting strategies by the DP algorithm. In this study, it is found that fuel consumption benefit can be obtained at a certain loss or even benefit of accumulative power reserve by an approximated linear slope factor of -5. This design method is verified through simulations of forward facing dynamic powertrain model. Finally, in order to further improve the fuel saving potential and the driveability, a Hybrid Electric PS-AMT prototype is introduced and design consideration concerning the optimal control strategy is discussed.

Shifting strategy for step change transmission vehicle : a comparative study and design method

The first prototype of an actuator for a new adaptive deformable mirror (DM) is presented together with the development of a 61-actuator grid element. The DM design consists of a thin membrane which acts as the correcting element. A grid of low voltage electro-magnetic push-pull actuators, impose out-of-plane displacements in the mirror's membrane. To provide a stable and stiff reference plane for the actuators, a mechanically stable and thermally decoupled honeycomb support structure is added. Several variants of variable reluctance actuators are considered. Each actuator consists of a closed magnetic circuit in which a strong permanent magnet (PM) provides a static magnetic force attracting ferromagnetic material. By applying a current through a coil which is situated around this magnet, this force can be influenced. Depending on the mechanical stiffness of the actuator, this leads to a certain displacement. Both the PM and the coil are connected to the fixed world and only the ferromagnetic material will move. The actuators are produced in arrays which make the design easy and extendable. The power dissipation in the actuator grid is in the order of milliwatts per actuator. Because of this low power dissipation active cooling is not required. The paper describes how the actuator stiffness and efficiency can be controlled. A test-setup is developed in which the actuator characteristics are measured.

/pdf/large-adaptive-deformable-mirror-design-and-first-prototypes-9tx97fx27j.pdf

M Maarten Steinbuch

Papers

State Estimator Design for Real-time Controlled Restraint Systems

Performance trade-offs in disturbance feedforward compensation of active hard-mounted vibration isolators

Second-order odd-harmonic repetitive control and its application to active filter control

Shifting strategy for step change transmission vehicle : a comparative study and design method

Large adaptive deformable mirror: design and first prototypes