M Maarten Steinbuch
Other affiliations: Nanyang Technological University, Delft University of Technology, Bosch ...read more
Bio: M Maarten Steinbuch is an academic researcher from Eindhoven University of Technology. The author has contributed to research in topic(s): Control theory & Feed forward. The author has an hindex of 51, co-authored 630 publication(s) receiving 11892 citation(s). Previous affiliations of M Maarten Steinbuch include Nanyang Technological University & Delft University of Technology.
Papers published on a yearly basis
TL;DR: Implementation of the CACC system, the string-stability characteristics of the practical setup, and experimental results are discussed, indicating the advantages of the design over standard adaptive-cruise-control functionality.
Abstract: The design of a cooperative adaptive cruise-control (CACC) system and its practical validation are presented. Focusing on the feasibility of implementation, a decentralized controller design with a limited communication structure is proposed (in this case, a wireless communication link with the nearest preceding vehicle only). A necessary and sufficient frequency-domain condition for string stability is derived, taking into account heterogeneous traffic, i.e., vehicles with possibly different characteristics. For a velocity-dependent intervehicle spacing policy, it is shown that the wireless communication link enables driving at small intervehicle distances, whereas string stability is guaranteed. For a constant velocity-independent intervehicle spacing, string stability cannot be guaranteed. To validate the theoretical results, experiments are performed with two CACC-equipped vehicles. Implementation of the CACC system, the string-stability characteristics of the practical setup, and experimental results are discussed, indicating the advantages of the design over standard adaptive-cruise-control functionality.
TL;DR: An extensive study on controlling the vehicular electric power system to reduce the fuel use and emissions, by generating and storing electrical energy only at the most suitable moments is presented.
Abstract: In the near future, a significant increase in electric power consumption in vehicles is expected. To limit the associated increase in fuel consumption and exhaust emissions, smart strategies for the generation, storage/retrieval, distribution, and consumption of electric power will be used. Inspired by the research on energy management for hybrid electric vehicles (HEVs), this paper presents an extensive study on controlling the vehicular electric power system to reduce the fuel use and emissions, by generating and storing electrical energy only at the most suitable moments. For this purpose, both off-line optimization methods using knowledge of the driving pattern and on-line implementable ones are developed and tested in a simulation environment. Results show a reduction in fuel use of 2%, even without a prediction of the driving cycle being used. Simultaneously, even larger reductions of the emissions are obtained. The strategies can also be applied to a mild HEV with an integrated starter alternator (ISA), without modifications, or to other types of HEVs with slight changes in the formulation.
TL;DR: The hitherto unravelled facts on the interactions of a cold atmospheric plasma with living cells and tissues are described.
Abstract: In this paper we describe the hitherto unravelled facts on the interactions of a cold atmospheric plasma with living cells and tissues. A specially designed source, plasma needle, is a low-power discharge, which operates under the threshold of tissue damage. When applied properly, the needle does not cause fatal cell injury which would result in cell death (necrosis). Instead, it allows precise and localized cell removal by means of the so-called cell detachment. In addition, plasma can be used for bacterial disinfection. Because of mild treatment conditions, plasma disinfection can be performed in vivo, e.g. on wounds and dental cavities. Presently, one strives to obtain a better control of the operating device. Therefore, plasma has been characterized using a variety of diagnostics, and a smart system has been designed for the positioning of the device with respect to the treated surface.
01 Dec 2002-Automatica
TL;DR: A robust repetitive controller structure is proposed that uses multiple memory-loops in a certain feedback configuration, such that small changes in period-time do not diminish the disturbance rejection properties.
Abstract: Repetitive control is useful if periodic disturbances act on a control system. Perfect (asymptotic) disturbance rejection is achieved if the period-time is exactly known. For those cases where the period-time changes and cannot be measured directly by an auxiliary signal, a robust repetitive controller structure is proposed. It uses multiple memory-loops in a certain feedback configuration, such that small changes in period-time do not diminish the disturbance rejection properties. The robust repetitive controller shows good implementation results for a tracking control problem of a Compact Disc player.
01 Apr 1990-Systems & Control Letters
TL;DR: A very simple method to compute a rather close lower bound on the H ∞ - norm, based on the relation between the singular values of the transfer function matrix and the eigenvalues of a related Hamiltonian matrix.
Abstract: A fast algorithm is presented to compute the H ∞ - norm of a transfer function matrix, based on the relation between the singular values of the transfer function matrix and the eigenvalues of a related Hamiltonian matrix The norm is computed with guaranteed accuracy A very simple method to compute a rather close lower bound on the H ∞ - norm is given
•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.
10 Mar 2009-Progress in Natural Science
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.
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.
01 Jan 2000
TL;DR: In this paper, the authors introduce a specific class of linear matrix inequalities (LMI) whose optimal solution can be characterized exactly, i.e., the optimal value equals the spectral radius of the operator.
Abstract: In the first part of this thesis, we introduce a specific class of Linear Matrix Inequalities (LMI) whose optimal solution can be characterized exactly. This family corresponds to the case where the associated linear operator maps the cone of positive semidefinite matrices onto itself. In this case, the optimal value equals the spectral radius of the operator. It is shown that some rank minimization problems, as well as generalizations of the structured singular value ($mu$) LMIs, have exactly this property. In the same spirit of exploiting structure to achieve computational efficiency, an algorithm for the numerical solution of a special class of frequency-dependent LMIs is presented. These optimization problems arise from robustness analysis questions, via the Kalman-Yakubovich-Popov lemma. The procedure is an outer approximation method based on the algorithms used in the computation of hinf norms for linear, time invariant systems. The result is especially useful for systems with large state dimension. The other main contribution in this thesis is the formulation of a convex optimization framework for semialgebraic problems, i.e., those that can be expressed by polynomial equalities and inequalities. The key element is the interaction of concepts in real algebraic geometry (Positivstellensatz) and semidefinite programming. To this end, an LMI formulation for the sums of squares decomposition for multivariable polynomials is presented. Based on this, it is shown how to construct sufficient Positivstellensatz-based convex tests to prove that certain sets are empty. Among other applications, this leads to a nonlinear extension of many LMI based results in uncertain linear system analysis. Within the same framework, we develop stronger criteria for matrix copositivity, and generalizations of the well-known standard semidefinite relaxations for quadratic programming. Some applications to new and previously studied problems are presented. A few examples are Lyapunov function computation, robust bifurcation analysis, structured singular values, etc. It is shown that the proposed methods allow for improved solutions for very diverse questions in continuous and combinatorial optimization.
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.