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Structured learning of rigid-body dynamics: A survey and unified view from a robotics perspective

GAMM Mitteilungen 2021年第2期44卷

作者： Geist, A. René Trimpe, Sebastian Intelligent Control Systems Group Max Planck Institute for Intelligent Systems Stuttgart Germany Institute for Data Science in Mechanical Engineering RWTH Aachen University Aachen Germany

Accurate models of mechanical system dynamics are often critical for model-based control and reinforcement learning. Fully data-driven dynamics models promise to ease the process of modeling and analysis, but require considerable amounts of data for training and often do not generalize well to unseen parts of the state space. Combining data-driven modeling with prior analytical knowledge is an attractive alternative as the inclusion of structural knowledge into a regression model improves the model's data efficiency and physical integrity. In this article, we survey supervised regression models that combine rigid-body mechanics with data-driven modeling techniques. We analyze the different latent functions (such as kinetic energy or dissipative forces) and operators (such as differential operators and projection matrices) underlying common descriptions of rigid-body mechanics. Based on this analysis, we provide a unified view on the combination of data-driven regression models, such as neural networks and Gaussian processes, with analytical model priors. Furthermore, we review and discuss key techniques for designing structured models such as automatic differentiation. © 2021 The Authors. GAMM - Mitteilungen published by Wiley-VCH GmbH.

关键词： Surveys

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Scenario-Based Thermal Management Parametrization Through Deep Reinforcement Learning

Scenario-Based Thermal Management Parametrization Through De...

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International Conference on Intelligent Transportation

作者： Thomas Rudolf Philip Muhl Sören Hohmann Lutz Eckstein department for Software Calibration and Diagnosis Porsche Engineering Group GmbH Weissach Germany department for Thermal Management Systems Dr. Ing. h.c. F. Porsche AG Weissach Germany Institute of Control System (IRS) Karlsruhe Institue of Technology (KIT) Karlsruhe Germany Institute for Automotive Engineering (ika) RWTH Aachen Aachen Germany

ISBN: (数字)9798331505929

ISBN: (纸本)9798331505936

The thermal system of battery electric vehicles demands advanced control. Its thermal management needs to effectively control active components across varying operating conditions. While robust control function parametrization is required, current methodologies show significant drawbacks. They consume considerable time, human effort, and extensive real-world testing. Consequently, there is a need for innovative and intelligent solutions that are capable of autonomously parametrizing embedded controllers. Addressing this issue, our paper introduces a learning-based tuning approach. We propose a methodology that benefits from automated scenario generation for increased robustness across vehicle usage scenarios. Our deep reinforcement learning agent processes the tuning task context and incorporates an image-based interpretation of embedded parameter sets. We demonstrate its applicability to a valve controller parametrization task and verify it in real-world vehicle testing. The results highlight the competitive performance to baseline methods. This novel approach contributes to the shift towards virtual development of thermal management functions, with promising potential of large-scale parameter tuning in the automotive industry.

关键词： Industries Technological innovation System dynamics Thermal management Valves Deep reinforcement learning Robustness Scenario generation Tuning Testing

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ERROR ANALYSIS OF KERNEL EDMD FOR PREDICTION AND control IN THE KOOPMAN FRAMEWORK

arXiv

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arXiv 2023年

作者： Philipp, Friedrich Schaller, Manuel Worthmann, Karl Peitz, Sebastian Nüske, Feliks Technische Universität Ilmenau Optimization-Based Control Group Institute for Mathematics Ilmenau Germany Optimization-Based Control Group Institute of Mathematics Technische Universität Ilmenau Ilmenau Germany Paderborn University Department of Computer Science Data Science for Engineering Germany Max Planck Institute for Dynamics of Complex Technical Systems Magdeburg Germany Department of Mathematics and Computer Science Freie Universität Berlin Germany

Extended Dynamic Mode Decomposition (EDMD) is a popular data-driven method to approximate the Koopman operator for deterministic and stochastic (control) systems. This operator is linear and encompasses full information on the (expected stochastic) dynamics. In this paper, we analyze a kernel-based EDMD algorithm, known as kEDMD, where the dictionary consists of the canonical kernel features at the data points. The latter are acquired by i.i.d. samples from a user-defined and application-driven distribution on a compact set. We prove bounds on the prediction error of the kEDMD estimator when sampling from this (not necessarily ergodic) distribution. The error analysis is further extended to control-affine systems, where the considered invariance of the Reproducing Kernel Hilbert Space is significantly less restrictive in comparison to invariance assumptions on an a-priori chosen dictionary. © 2023, CC BY.

关键词： Dynamic mode decomposition

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Geometric Parameterized Macromodel of Uniaxial Capacitance Accelerometer Based on Modal Superposition

Geometric Parameterized Macromodel of Uniaxial Capacitance A...

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International Conference on Actual Problems of Electronic Instrument engineering (APEIE)

作者： Aleksandr V. Gridchin Aleksei N. Koleda Evgenii S. Barbin Tamara G. Nesterenko Vladimir A. Kolchuzhin Department of Semiconductor Devices and Microelectronics Novosibirsk State Technical University Novosibirsk Russia Department of Electronic Engineering National Research Tomsk Polytechnic University Tomsk Russia Laboratory of Intelligent Computer Systems Tomsk State University of Control Systems and Radioelectronics Tomsk Russia Advanced Cellular Group Qorvo Munich GmbH Munich Germany

The paper presents a piecewise geometric parameterization method and a parametric analysis of uniaxial capacitance accelerometer using a reduced model formulated on the modal superposition method. The extraction of parameters for the macromodel such as modal frequencies, modal masses, modal stiffnesses, strain energy, and capacitances are described. The reduced model consists of the two modes: torsion mode, and transversal mode, three electrodes in the electrostatic domain, and eight master nodes in the geometrical domain located at the edges of the plate. The generation of the discrete macromodels is executed using commercial software. The thickness of the plate has been selected as a design parameter. Linear piecewise interpolation is used for macromodel parameterization which have been done inside VHDL-AMS code. The accelerometer’s dynamic response simulated using of parametrized macromodel considering the mechanical contact phenomena and the nonlinear electrostatic interaction are presented and discussed. The developed approach can be applied for fast system level simulations in view of the variation of the geometric parameters.

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Modeling, analysis and experimental observations of fat volume properties in compartmental models for drug pharmacokinetics

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Annual Reviews in control 2025年 60卷

作者： Ynineb, Amani R. Khoumeri, Bouchra Yumuk, Erhan Ayvaz, Bora Ben Othman, Ghada Ionescu, Clara M. Copot, Dana Ghent University Department of Electromechanics Systems and Metal Engineering Research Group on Dynamical Systems and Control Technologiepark 125 Gent 9052 Belgium Istanbul Technical University Department of Control and Automation Engineering Istanbul 34469 Turkey

Drug related dynamic uptake, clearance and anomalous diffusion patterns are dependent of biological tissue composition. Of particular importance is the fat volume, where drug trapping occurs in long term usage and related to lipophilic properties of drugs and non-homogeneous mixing. This paper introduces three probable drug pathways from fat volumes to augmented compartments, herein called trap volumes. In silico validation by using patient simulators with body mass index larger than 25. A non-homogeneous drug diffusion in biological tissue was considered using the partial-Caputo fractional-order compartmental model. To understand the effects in potential monitoring and sensing data information systems, an experiment has been proposed for in vitro impedance spectroscopy of fat samples. Variability with fat volume in observed data confirms the fractional-order characteristics that support theoretical model assumptions. A discussion section provides the implications for control of drug delivery systems. © 2025 The Authors

关键词： Compartmental model Digital simulator Experimental validation Fractal kinetics Fractional-order impedance model Pharmacology Spectroscopy

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Optimal trajectory planning of complicated robotic timber joints based on particle swarm optimization and an adaptive genetic algorithm

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Construction Robotics 2021年第2期5卷 131-146页

作者： Meng, Yiping Sun, Yiming Chang, Wen-shao People Environments and Performance Group School of Architecture The University of Sheffield Sheffield UK Department of Automatic Control and Systems Engineering The University of Sheffield Sheffield UK

In this paper, a methodology for path distance and time synthetic optimal trajectory planning is described in order to improve the work efficiency of a robotic chainsaw when dealing with cutting complex timber joints. To demonstrate this approach one specific complicated timber joint is used as an example. The trajectory is interpolated in the joint space by using a quantic polynomial function which enables the trajectory to be constrained in the kinematic limits of velocity, acceleration, and jerk. The particle swarm optimization (PSO) is applied to optimize the path of all cutting surfaces of the timber joint in operating space to achieve the shortest path. Based on the optimal path, an adaptive genetic algorithm (AGA) is used to optimize the time interval of interpolation points of every joint to realize the time-optimal trajectory. The results of the simulation show that the PSO method shortens the distance of the trajectory and that the AGA algorithm reduces time intervals and helps to obtain smooth trajectories, validating the effectiveness and practicability of the two proposed methodology on path and time optimization for 6-DOF robots when used in cutting tasks.

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Design and Analysis of Individually Demagnetized Power Converter for Switched Reluctance Motors

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IEEE Transactions on Transportation Electrification 2025年第3期11卷 8439-8449页

作者： Liu, Hemiao Chen, Hao Wang, Xing Gorbounov, Yassen Wheeler, Patrick Anuchin, Alecksey Demidova, Galina Korovkin, Nikolay Liudmila, Sakhno Shenzhen Research Institute China University of Mining and Technology Shenzhen515100 China China University of Mining and Technology School of Electrical Engineering Xuzhou221116 China Xinjiang Institute of Engineering Ürümqi830000 China International Joint Research Center of Central and Eastern European Countries on New Energy Electric Vehicle Technology and Equipment Xuzhou221008 China International Cooperation Joint Laboratory of New Energy Power Generation and Electric Vehicles of Jiangsu Province Colleges and Universities Xuzhou221008 China Xuzhou Key Laboratory of New Energy Electric Vehicle Technology and Equipment Xuzhou221008 China Mining Production University of Mining and Geology "St. Ivan Rilski " Department of Automation Sofia1700 Bulgaria The University of Nottingham Power Electronics Machines and Control Group NottinghamNG7 2RD United Kingdom Electric Drives Department Moscow111250 Russia Saint-Petersburg National Research University of Information Technologies Mechanics and Optics Faculty of Control Systems and Robotics Engineer Saint Petersburg197101 Russia Peter the Great St. Petersburg Polytechnic University Institute of Energy Saint Petersburg195251 Russia

Switched reluctance motors (SRMs) are capable of operating at high speeds and high loads. The large back EMF results in the excitation winding current being demagnetized more slowly, which, in turn, reduces the efficiency and output of the motor system. This study proposes a novel individually demagnetization power converter (IDPC) specifically designed for SRMs to effectively use the demagnetization energy through an independent demagnetization circuit. Compared with traditional converters, the IDPC can accept direct current (dc) and high-frequency ac inputs while achieving fast demagnetization and energy recovery. The topology and working principle of the IDPC are analyzed in detail in this article using a three-phase 12/8 SRM as the research object. In addition, the influence of the winding demagnetization voltage on the negative torque during the demagnetization phase was studied, as well as the functional implementation and logic control strategy of the IDPC. Simulation and experimental results confirm the validity of the proposed topology and high-frequency ac drive characteristics, as well as their advantages in terms of efficiency, output capacity, and dynamic performance. © 2015 IEEE.

关键词： Reluctance motors

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A Comparison Analysis between Two and Three Levels Inverter to Grid-Connected Used the Photovoltaic System

A Comparison Analysis between Two and Three Levels Inverter ...

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Electronics, Energy and Measurement (IC2EM), International Conference on

作者： Fayçal Hadj Mihoub Sidi Moussa Abdelkader Morsli Abdelhalim Tlemçani Hocine Belmili Hassan Nouri Electrical Engineering and Automation Research Laboratory (LREA) University of Medea Medea Algeria Renewable Energy Development Center (CDER) Bou-Ismail Solar Equipment Development Unit (UDES) Tipaza Algeria Department of Engineering Design and Mathematics Power Systems Electronics and Control Research Group Bristol U.K.

This article presents a comparative study of two topologies of three-phase photovoltaic inverters connected to the grid, between the usual two-level inverter and three-level NPC (Neutral Point Clamped) inverter. Inverter control and the boost converter MPPT controller are based on the SRF-dq method and the INC algorithm respectively. The comparison relies on evaluating the overall efficiency and harmonic distortion of the inverter. All circuits are modeled and simulated using Matlab-Simulink. The results obtained indicate satisfaction with the quality, of the current and voltage injected into the electrical grid, and reflect that both inverters are efficient and comply with IEEE-519 standard recommendations, but the three-level inverter performs better results than the two-level inverter.

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Learning Fast and Precise Pixel-to-Torque control

arXiv

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arXiv 2022年

作者： Bleher, Steffen Heim, Steve Trimpe, Sebastian Intelligent Control Systems Group Max Planck Institute for Intelligent Systems Stuttgart Germany Biomimetic Robotics Lab Massachusetts Institute of Technology Cambridge United States Institute for Data Science in Mechanical Engineering RWTH Aachen University Aachen Germany

In the field, robots often need to operate in unknown and unstructured environments, where accurate sensing and state estimation (SE) becomes a major challenge. Cameras have been used to great success in mapping and planning in such environments, as well as complex but quasi-static tasks such as grasping, but are rarely integrated into the control loop for unstable systems. Learning pixel-to-torque control promises to allow robots to flexibly handle a wider variety of tasks. Although they do not present additional theoretical obstacles, learning pixel-to-torque control for unstable systems that that require precise and high bandwidth control still poses a significant practical challenge, and best practices have not yet been established. To help drive reproducible research on the practical aspects of learning pixel-to-torque control, we propose a platform that can flexibly represent the entire process, from lab to deployment, for learning pixel-to-torque control on a robot with fast, unstable dynamics: the vision-based Furuta pendulum. The platform can be reproduced with either off-the-shelf or custom-built hardware. We expect that this platform will allow researchers to quickly and systematically test different approaches, as well as reproduce and benchmark case studies from other labs. We also present a first case study on this system using DNNs which, to the best of our knowledge, is the first demonstration of learning pixel-to-torque control on an unstable system with update rates faster than 100 Hz. A video synopsis can be found online at https://***/S2llScfG-8E, and in the supplementary material. © 2022, CC BY.

关键词： Torque control

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Informed sampling-based trajectory planner for automated driving in dynamic urban environments

arXiv

引用

arXiv 2022年

作者： Smit, Robin van der Ploeg, Chris Teerhuis, Arjan Silvas, Emilia Netherlands Organisation for Applied Scientific Research Integrated Vehicle Safety Group Helmond5700 AT Netherlands Eindhoven University of Technology Dynamics and Control Group Mechanical Engineering Dept. P.O. Box 513 Eindhoven5600 MB Netherlands Eindhoven University of Technology Control Systems Technology Group Mechanical Engineering Dept. P.O. Box 513 Eindhoven5600 MB Netherlands

The urban environment is amongst the most difficult domains for autonomous vehicles. The vehicle must be able to plan a safe route on challenging road layouts, in the presence of various dynamic traffic participants such as vehicles, cyclists and pedestrians and in various environmental conditions. The challenge remains to have motion planners that are computationally fast and that account for future movements of other road users proactively. This paper describes an computationally efficient sampling-based trajectory planner for safe and comfortable driving in urban environments. The planner improves the Stable-Sparse-RRT algorithm by adding initial exploration branches to the search tree based on road layout information and reiterating the previous solution. Furthermore, the trajectory planner accounts for the predicted motion of other traffic participants to allow for safe driving in urban traffic. Simulation studies show that the planner is capable of planning collision-free, comfortable trajectories in several urban traffic scenarios. Adding the domain-knowledge-based exploration branches increases the efficiency of exploration of highly interesting areas, thereby increasing the overall planning performance. Copyright © 2022, The Authors. All rights reserved.

关键词： Trajectories

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