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arXiv 2022年

作者： Dey, Sharmita Fan, David Schmid, Robin Dixit, Anushri Otsu, Kyohei Touma, Thomas Schilling, Arndt F. Agha-Mohammadi, Ali-Akbar NASA Jet Propulsion Laboratory California Institute of Technology PasadenaCA United States The University of Goettingen University Medical Center Goettingen Germany The Institute for Robotics and Intelligent Machines Georgia Institute of Technology AtlantaGA United States Zurich8092 Switzerland Control and Dynamical Systems California Institute of Technology PasadenaCA United States Mechanical and Civil Engineering California Institute of Technology PasadenaCA United States

Legged robots can traverse a wide variety of terrains, some of which may be challenging for wheeled robots, such as stairs or highly uneven surfaces. However, quadruped robots face stability challenges on slippery surfaces. This can be resolved by adjusting the robot's locomotion by switching to more conservative and stable locomotion modes, such as crawl mode (where three feet are in contact with the ground always) or amble mode (where one foot touches down at a time) to prevent potential falls. To tackle these challenges, we propose an approach to learn a model from past robot experience for predictive detection of potential failures. Accordingly, we trigger gait switching merely based on proprioceptive sensory information. To learn this predictive model, we propose a semi-supervised process for detecting and annotating ground truth slip events in two stages: We first detect abnormal occurrences in the time series sequences of the gait data using an unsupervised anomaly detector, and then, the anomalies are verified with expert human knowledge in a replay simulation to assert the event of a slip. These annotated slip events are then used as ground truth examples to train an ensemble decision learner for predicting slip probabilities across terrains for traversability. We analyze our model on data recorded by a legged robot on multiple sites with slippery terrain. We demonstrate that a potential slip event can be predicted up to 720 ms ahead of a potential fall with an average precision greater than 0.95 and an average F-score of 0.82. Finally, we validate our approach in real-time by deploying it on a legged robot and switching its gait mode based on slip event detection. © 2022, CC BY-NC-SA.

关键词： Robots

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Network Inference using Sinusoidal Probing

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IFAC-PapersOnLine 2021年第9期54卷 696-700页

作者： Robin Delabays Melvyn Tyloo Automatic Control Laboratory Swiss Federal Institute of Technology CH-8092 Zurich Switzerland Center for Control Dynamical Systems and Computation UCSB Santa Barbara CA 93106-5070 USA School of Engineering University of Applied Sciences of Western Switzerland HES-SO CH-1951 Sion Switzerland Institute of Physics École Polytechnique Fédérale de Lausanne (EPFL) CH-1015 Lausanne Switzerland

The aim of this manuscript is to present a non-invasive method to recover the network structure of a dynamical system. We propose to use a controlled probing input and to measure the response of the network, in the spirit of what is done to determine oscillation modes in large electrical networks. For a large class of dynamical systems, we show that this approach is analytically tractable and we confirm our findings by numerical simulations of networks of Kuramoto oscillators. Our approach also allows us to determine the number of agents in the network by probing and measuring a single one of them.

关键词： Networks inference processes Jacobian matrices input signals low frequencies

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Reconstructing Network Structures from Partial Measurements

Research Square

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Research Square 2021年

作者： Tyloo, Melvyn Delabays, Robin Jacquod, Philippe School of Engineering University of Applied Sciences of Western Switzerland HES-SO SionCH-1951 Switzerland Automatic Control Laboratory ETH Zürich ZürichCH-8092 Switzerland Center for Control Dynamical Systems and Computation UC Santa Barbara Santa BarbaraCA93106-5070 United States Department of Quantum Matter Physics University of Geneva GenevaCH-1211 Switzerland

The dynamics of systems of interacting agents is determined by the structure of their coupling network. The knowledge of the latter is therefore highly desirable, for instance to develop efficient control schemes, to accurately predict the dynamics or to better understand inter-agent processes. In many important and interesting situations, the network structure is not known, however, and previous investigations have shown how it may be inferred from complete measurement time series, on each and every agent. These methods implicitly presuppose that, even though the network is not known, all its nodes are. A major shortcoming of theirs is that they cannot provide any reliable information, not even on partial network structures, as soon as some agents are unobservable. Here, we construct a novel method that determines network structures even when not all agents are measurable. We establish analytically and illustrate numerically that velocity signal correlators encode not only direct couplings, but also geodesic distances in the coupling network, within the subset of measurable agents. When dynamical data are accessible for all agents, our method is furthermore algorithmically more efficient than the traditional ones, because it does not rely on matrix inversion. © 2021, CC BY.

关键词： Correlators

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Stable robust controller inspired by the mammalian limbic system for a class of nonlinear systems

Stable robust controller inspired by the mammalian limbic sy...

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American control Conference

作者： Ignacio Rubio Scola Luis Rodolfo Garcia Carrillo Joao P. Hespanha Department of Mathematics CIFASIS (CONICET-UNR) Rosario Argentina Unmanned Systems Laboratory Texas A&M University Corpus Christi Texas USA Center for Control Dynamical Systems and Computation University of California Santa Barbara CA USA

ISBN: (数字)9781538682661

ISBN: (纸本)9781538682678

In recent years diverse computational models of emotional learning observed in the mammalian brain have inspired a number of self-learning control approaches. These architectures are promising in terms of their learning ability and low computational cost. However, the lack of rigorous stability analysis and mathematical proofs of stability and performance has limited the proliferation of these controllers. To address this drawback, this paper proposes a modified brain emotional neural network structure using a radial basis function inside the Thalamus and an emotional signal based on an integral action structure to increase performance. Mathematical stability proofs are provided, together with numerical simulations, demonstrating the superior performance obtained with the new modifications proposed to the emoional learning-inspired control.

关键词： Thalamus Mathematical model Stability analysis Artificial neural networks Brain modeling Nonlinear systems Computational modeling

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Game Theoretic Potential Field for Autonomous Water Surface Vehicle Navigation Using Weather Forecasts

Game Theoretic Potential Field for Autonomous Water Surface ...

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American control Conference

作者： Evan Krell Luis Rodolfo Garcia Carrillo Scott A. King Joao P. Hespanha Control of Robots and Autonomous Agents Laboratory (CORAL) Texas A&M University Corpus Christi CORAL and the Unmanned Systems Laboratory (TAMUCC-USL) School of Engineering & Computing Sciences Texas A&M University Corpus Christi Center for Control Dynamical Systems and Computation University of California Santa Barbara CA USA

ISBN: (数字)9781538682661

ISBN: (纸本)9781538682678

Imperfect weather forecasts complicate robot planning. A conservative motion planning algorithm is developed to address uncertainty in autonomous boat missions. Dynamic Programming generates an optimal action for every location and game theory strategically handles uncertainty. Experimental results using Massachusetts Bay forecasts show the robot is able minimize the cost of worst-case weather.

关键词： Robots Planning Force Games Heuristic algorithms Weather forecasting

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Heavy-Tailed Distribution of the Number of Papers within Scientific Journals

arXiv

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arXiv 2020年

作者： Delabays, Robin Tyloo, Melvyn Center for Control Dynamical Systems and Computation UC Santa Barbara Santa BarbaraCA93106 United States Theoretical Division Los Alamos National Laboratory Los AlamosNM87545 United States

Scholarly publications represent at least two benefits for the study of the scientific community as a social group. First, they attest of some form of relation between scientists (collaborations, mentoring, heritage,...), useful to determine and analyze social subgroups. Second, most of them are recorded in large data bases, easily accessible and including a lot of pertinent information, easing the quantitative and qualitative study of the scientific community. Understanding the underlying dynamics driving the creation of knowledge in general, and of scientific publication in particular can contribute to maintaining a high level of research, by identifying good and bad practices in science. In this article, we aim at advancing this understanding by a statistical analysis of publication within peer-reviewed journals. Namely, we show that the distribution of the number of papers published by an author in a given journal is heavy-tailed, but has lighter tail than a power law. Interestingly, we demonstrate (both analytically and numerically) that such distributions match the result of an modified preferential attachment process, where, on top of a Barabási-Albert process, we take finite career span of scientists into account. © 2020, CC BY.

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Utilizing ARMA Models for System Identification in Stirred Tank Heater: Different Approaches

Computing Open

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Computing Open 2023年第1期computing-open卷

作者： Kiavash Hossein Sadeghi Abolhassan Razminia Arash Marashian https://***/0009-0002-5493-8857 Dynamical Systems & Control (DSC) Research Laboratory Department of Electrical Engineering School of Engineering Persian Gulf University 75169 Boushehr Iran https://***/0000-0001-5139-4255 Åbo Akademi University Turku Finland https://***/0000-0001-6117-7377

Since system identification is a substantial part of many control algorithms, attaining a suitable model is necessary. In this paper, as a novelty, six standard identification methods are used so as to identify the linear ARMA forms of the proposed, widely used model of stirred tank heater. We have chosen these six methods because these methods fit to our desire for the parameter estimation of the ARMA model and they are new and applicable for modeling of all fields of engineering and systems. Beyond that, the mathematics of these methods are so easy to apply and they provide enough data for identifying a wide variation of systems. Furthermore, these algorithms are brought up in a simple and concise manner and easy to implement. In addition, the mathematical form of the suggested stirred tank heater is presented. Furthermore, identification methods are compared in terms of some measures, such as rate of convergence and produced error. Finally, the effectiveness of the six presented identification methods for estimating the stirred tank heater model is illustrated.

关键词： System identification two-stage identification stirred tank heater

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WITHDRAWN: Rethinking the Micro-Foundation of Opinion Dynamics: Rich Consequences of an Inconspicuous Change

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IFAC-PapersOnLine 2020年第5期53卷 307-310页

作者： Wenjun Mei Francesco Bullo Ge Chen Julien M. Hendrickx Florian Dörfler Automatic Control Laboratory ETH Zurich 8006 Zurich Switzerland Center for Control Dynamical Systems and Computation University of California Santa Barbara CA 93106 USA Academy of Mathematics and Systems Science Chinese Academy of Science Beijing 100190 China Institute of Information and Communication Technologies Electronics and Applied Mathematics Université catholique de Louvain Louvain-la-Neuve B-1348 Belgium

This article has been withdrawn: please see Elsevier Policy on Article Withdrawal ( http://***/locate/withdrawalpolicy ). This article has been withdrawn at the request of the editor and publisher. The publisher regrets that an error occurred which led to the premature publication of this paper. This error bears no reflection on the article or its authors. The publisher apologizes to the authors and the readers for this unfortunate error.

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System size identification from sinusoidal probing in diffusive complex networks

arXiv

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arXiv 2020年

作者： Tyloo, Melvyn Delabays, Robin School of Engineering University of Applied Sciences of Western Switzerland HES-SO SionCH-1951 Switzerland Automatic Control Laboratory ETH Zurich ZurichCH-8092 Switzerland Center for Control Dynamical Systems and Computation UC Santa Barbara Santa BarbaraCA93106-5070 United States

One of the most fundamental characteristic of a complex system is its size (or volume), which, in many modelling, is represented by the number of its individual components. Complex systems under investigation nowadays are typically large and/or time-varying, rendering their identification challenging. We propose here an accurate and efficient method to determine the size of (i.e., number of agents in) a complex, diffusively coupled dynamical system, that leverages the response of the system to an injected probing signal. For our method to be applicable, we rely on some assumptions on system's characteristics, namely, on the spectrum of the coupling graph and on the basin stability of its steady state(s). Even though such assumptions imply that our method cannot be applied to any instance of diffusively coupled group of dynamical agents, we argue that it covers relevant and interesting examples. Furthermore, the simplicity of the approach and its low computational complexity renders it very interesting for the systems to which it applies. © 2020, CC BY.

关键词： Complex networks

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Classical and Advanced control Methods Applied to an Anaerobic Digestion Reactor Model

Classical and Advanced Control Methods Applied to an Anaerob...

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CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON)

作者： E. Fernandez W. Ipanaque R. Cajo R. De Keyser Automatic and Control Systems laboratory Piura University Piura Perú Automatic and Control Systems lab Piura University Piura Peru Faculty of Engineering and Architecture Research group on Dynamical Systems and Control Ghent University Gent Belgium Faculty of Engineering and Architecture Research group on Dynamical Systems and Control Ghent University Ghent Belgium

ISBN: (纸本)9781728131863

In this work, advanced method of process control as Extended Prediction Self-Adaptive control (EPSAC) and Nonlinear Extended Prediction Self-Adaptive control (NEPSAC) are implemented and compared with the traditional PID controller tuned by a novel KC autotuning method and a classical FRtool method. The controllers are designed based on a linear and non-linear reactor model of the Anaerobic digestion pilot plant located in Peru. The performance evaluation of the controllers is realized through MATLAB environment with model parameters obtained experimentally. Also, a linear model has been developed using a novel estimation method of a Second Order Plus Dead-Time models (SOPDT). The results show that NEPSAC outperforms the other controllers.

关键词： adaptive control bioreactors linear systems nonlinear control systems predictive control process control temperature control three-term control Process control Three term control systems Nonlinear control systems Predictive control Temperature control adaptive control Bioreactors Linear system Proportional Integral Derivative control controllers control Methods DEAD TIME Anaerobic digestion anaerobic treatment Advanced controls

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