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Robust Finite-Time Containment of Networked Heterogeneous Nonlinear Systems with Intermittent Measurement Only

IEEE Transactions on Network Science and engineering 2025年

作者： Tian, Biao Zhang, Hao Cui, Peiyu Wang, Zhuping Yan, Huaicheng Shanghai Key Laboratory of Wearable Robotics and Human-Machine Interaction Tongji University College of Electronic and Information Engineering Department of Control Science and Engineering Shanghai201804 China Ministry of Education Shanghai Institute of Intelligent Science and Technology National Key Laboratory of Autonomous Intelligent Unmanned Systems Frontiers Science Center for Intelligent Autonomous Systems China East China University of Science and Technology School of Information Science and Engineering Shanghai200237 China

The robust finite-time containment problem of fully heterogeneous multiagent systems with uncertainties is often challenging, especially when only intermittent output measurement is used. To address the issue posed by the nonidentical system dynamics of multiple leaders, which makes the traditional distributed estimator form for the convex hull inapplicable, a distributed finite-time estimator is constructed for each follower to extract the system matrices and states of leaders. Then, in the output-triggering setting, a finite-time extended state observer driven by intermittent output measurement is developed to reconstruct the uncertainties and unmeasurable states of followers. Meanwhile, the non-continuous output measurement will lead to the differentiation of virtual control laws undefined. To solve this issue, a filtering compensation scheme-based finitetime controller via the backstepping technique is developed for nonlinear followers, ensuring practical finite-time stability (PFTS) of the closed-loop system. It is shown that the proposed algorithm steers each follower into the preset convex combination spanned by the positions of multiple leaders. The capability of the exploited control protocol is verified through simulations and experiments. 2013 IEEE.

关键词： Backstepping

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Neurocontroller for vibrodrive control of adaptive vibration technological machines 2

Neurocontroller for vibrodrive control of adaptive vibration...

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2nd IEEE KhPI Week on Advanced Technology, KhPI Week 2021

作者： Chubyk, Roman Zelinsky, Igor Cherno, Oleksandr Lviv National Agrarian University Department of Information Systems and Technologies Lviv Ukraine Technologies Institute of Mechanical Engineering and Transport Lviv Polytechnic National University Department of Robotics and Integrated Mechanical Engineering Lviv Ukraine Admiral Makarov National University of Shipbuilding Department of Computerized Control Systems Mykolaiv Ukraine

A structure of the neurocontroller-based control system for the vibratory drive of adaptive vibration technological machines is proposed. It allows implementing a two-circuit system of neurocontrol of energy and techn... 详细信息

ISBN: (纸本)9781665412056

关键词： Model predictive control

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Form-finding of tensegrity structures utilizing a nonlinear fletcher-reeves conjugate gradient method

Form-finding of tensegrity structures utilizing a nonlinear ...

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2021 IEEE International Conference on Real-Time Computing and robotics, RCAR 2021

作者： Zhao, Liming Liu, Keping Li, Chunxu Jin, Long Sun, Zhongbo Changchun University of Technology Department of Control Engineering Changchun130021 China Centre for Robotics and Neural Systems University of Plymouth PlymouthPL48AA United Kingdom School of Information Science and Engineering Lanzhou University Lanzhou730000 China

ISBN: (纸本)9781665436786

In the domain of soft tensegrity robot, the self-equilibrium tensegrity structure is vital for the further analysis of robot's locomotion. Furthermore, form-finding is an important step for finding a self-equilibrium tensegrity structure. In this paper, a conjugate gradient form-finding (CGFF) algorithm is developed and investigated for the form-finding problems of tensegrity systems. Besides, a Fletcher-Reeves conjugate gradient method is employed to solve the nonlinear unconstrained optimization problems which transformed from the form-finding problems. Moreover, the initial conditions of the tensegrity structure such as the axial stiffness and rest lengths of the element have been utilized to explore the configuration details of the self-equilibrium tensegrity system. Eventually, several numerical simulations are provided to verify the accuracy and high-efficiency of the CGFF form-finding algorithm. © 2021 IEEE.

关键词： Conjugate gradient method

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Application of Deep Learning Method to Estimate Bottomhole Pressure Dynamics of Oil Wells

Application of Deep Learning Method to Estimate Bottomhole P...

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IEEE International Symposium on Industrial Electronics (ISIE)

作者： Haibo Cheng Shichao Li Peng Zeng Valeriy Vyatkin State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China Department of Computer Science Electrical and Space Engineering Luleå University of Technology Luleå Sweden Department of Electrical Engineering and Automation Aalto University Helsinki Finland

Surrogate models, which have become an effective and popular method to close loop reservoir management problems, use a data-driven approach to predict dynamic injection and production wells parameters and optimize waterflooding development. In this study, a deep learning-based surrogate model method is proposed to estimate bottomhole pressure (BHP) of production wells in waterflooding reservoirs. Bidirectional long short-term memory (BiLSTM) network, as an efficient deep learning approach, is applied to BHP estimation using fluctuation data. Extended Fourier amplitude sensitivity test (EFAST) method is employed to analyse the influence of different input factors on BHP dynamics, and a reduced dataset is rebuilt to predict BHP parameter based on BiLSTM-EFAST algorithm. The estimation results are tested on a dataset from Volve oilfield in North Sea, and compared with other deep learning methods. The test results indicate that the proposed method can achieve higher prediction accuracy. A reduced dataset-based approach provides a new attempt to reduce model complexity and improve calculation speed for big data-driven surrogate model in oil and gas industry.

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A Signal Temporal Logic Planner for Ergonomic Human–Robot Collaboration

A Signal Temporal Logic Planner for Ergonomic Human–Robot C...

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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Giuseppe Silano Amr Afifi Martin Saska Antonio Franchi Department of Cybernetics Faculty of Electrical Engineering Czech Technical University in Prague Prague Czech Republic Robotics and Mechatronics Department Electrical Engineering Mathematics and Computer Science (EEMCS) Faculty University of Twente AE Enschede The Netherlands Department of Computer Control and Management Engineering Sapienza University of Rome Rome Italy LAAS-CNRS Université de Toulouse Toulouse France

This paper proposes a method for designing human-robot collaboration tasks and generating corresponding trajectories. The method uses high-level specifications, expressed as a Signal Temporal Logic (STL) formula, to automatically synthesize task assignments and trajectories. To illustrate the approach, we focus on a specific task: a multi-rotor aerial vehicle performing object handovers in a power line setting. The motion planner considers limitations, such as payload capacity and recharging constraints, while ensuring that the trajectories are feasible. Additionally, the method enables users to specify robot behaviors that take into account human comfort (e.g., ergonomics, preferences) while using high-level goals and constraints. The approach is validated through numerical analyzes in MATLAB and realistic Gazebo simulations using a mock-up scenario.

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Direct LiDAR-Inertial Odometry: Lightweight LIO with Continuous-Time Motion Correction

Direct LiDAR-Inertial Odometry: Lightweight LIO with Continu...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Kenny Chen Ryan Nemiroff Brett T. Lopez Department of Electrical and Computer Engineering University of California Los Angeles Los Angeles CA USA Verifiable and Control-Theoretic Robotics Laboratory University of California Los Angeles Los Angeles CA USA Department of Mechanical and Aerospace Engineering University of California Los Angeles Los Angeles CA USA

Aggressive motions from agile flights or traversing irregular terrain induce motion distortion in LiDAR scans that can degrade state estimation and mapping. Some methods exist to mitigate this effect, but they are still too simplistic or computationally costly for resource-constrained mobile robots. To this end, this paper presents Direct LiDAR-Inertial Odometry (DLIO), a lightweight LiDAR-inertial odometry algorithm with a new coarse-to-fine approach in constructing continuous-time trajectories for precise motion correction. The key to our method lies in the construction of a set of analytical equations which are parameterized solely by time, enabling fast and parallelizable point-wise deskewing. This method is feasible only because of the strong convergence properties in our nonlinear geometric observer, which provides provably correct state estimates for initializing the sensitive IMU integration step. Moreover, by simultaneously performing motion correction and prior generation, and by directly registering each scan to the map and bypassing scan-to-scan, DLIO's condensed architecture is nearly 20% more computationally efficient than the current state-of-the-art with a 12% increase in accuracy. We demonstrate DLIO's superior localization accuracy, map quality, and lower computational overhead as compared to four state-of-the-art algorithms through extensive tests using multiple public benchmark and self-collected datasets.

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Development of a Sphere Motion Measurement System and Evaluation of the Roller Arrangement Requirement

Development of a Sphere Motion Measurement System and Evalua...

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International Conference on Ubiquitous Robots (UR)

作者： Shota Chikushi Kenji Kimura Jonghyun Ahn Kazuo Ishii Department of Robotics Kindai University Higashi-Hiroshima-shi Hiroshima Japan Department of Control Engineering National Institute of Technology Matsue College Matsue-shi Shimane Japan Department of Intelligent Mechanical Engineering Hiroshima Institute of Technology Hiroshima-shi Hiroshima Japan Department of Human Intelligence Systems Kyushu Institute of Technology Kitakyushu-shi Fukuoka Japan

To conserve human resources and labor, there is a demand for robots to transport objects. Compared to previous object transport methods, sphere transport by a mobile robot is efficient for transporting objects without loading them and while on the ground. However, previous research on sphere transport has not clarified the methodology for designing and controlling sphere transport based on kinematic and dynamic properties. Therefore, this study attempts to develop a rollersphere motion measurement method for focusing on the roller angular velocity and to evaluate the effectiveness of the roller arrangement requirement. In particular, this study evaluates the “roller arrangement requirement,” which is necessary for roller arrangement (position/orientation) considering kinematic characteristics in sphere transport. Experiments have shown the effectiveness of the roller arrangement requirement with a novel roller-sphere motion measurement method.

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Optimal control of Automatic Manipulator for Elimination of Galvanic Line Load Oscillation

Periodica polytechnica Electrical engineering and computer s...

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Periodica polytechnica Electrical engineering and computer science 2021年第2期65卷 91-105页

作者： Autsou, Siarhei Rassõlkin, Anton Vaimann, Toomas Demidova, Galina Saroka, Viktor Karpovich, Dzmitry Kallaste, Ants Department of Automation of Production Processes and Electrical Engineering Faculty of Chemical Technology and Technique Belarussian State Technological University 13a Sverdlova str. Minsk220006 Belarus Department of Electrical Power Engineering and Mechatronics Tallinn University of Technology 5 Ehitajate street Tallinn19086 Estonia Faculty of Control Systems and Robotics Itmo University 49 Kronverksky Pr. St. Petersburg197101 Russia

This paper provides an analysis of the current state-of-The-Art technologies in the field of auto-operators used in production during the electroplating process. General schemes of operations are presented, benefits and drawbacks of each scheme are discussed. The paper discusses an increase in the operating efficiency of the auto-operator in transient conditions (braking and acceleration) by reducing suspension oscillations and provides an example of a similar problem from other industries. In addition to the classification of the auto-operators, three main ways and control methods of the auto-operator of a galvanic line are presented. The main ways of eliminating oscillations during the movement of the auto-operator, as well as the rationale for the choice of adaptive (optimal) control, based on and comparing the basic control algorithms of the robot manipulator, are discussed. The comparative analysis of algorithms used to determine the optimal control has been carried out. Application field of each optimal control method described, moreover advantages and disadvantages as well as implementation methods described. Bellman dynamic programming method was chosen to eliminate oscillations of the suspension with details during the auto-operator transient conditions, the chosen method takes into account all necessary conditions to achieve the desired result. © 2021 Budapest University of Technology and Economics. All rights reserved.

关键词： Dynamic programming

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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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iMTSP: Solving Min-Max Multiple Traveling Salesman Problem with Imperative Learning

arXiv

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arXiv 2024年

作者： Guo, Yifan Ren, Zhongqiang Wang, Chen The Flight Dynamics & Control/Hybrid Systems Lab Purdue University West LafayetteIN47907 United States Robotics Institute Carnegie Mellon University PittsburghPA15213 United States Lab Department of Computer Science and Engineering University at Buffalo NY14260 United States

This paper considers a Min-Max Multiple Traveling Salesman Problem (MTSP), where the goal is to find a set of tours, one for each agent, to collectively visit all the cities while minimizing the length of the longest tour. Though MTSP has been widely studied, obtaining near-optimal solutions for large-scale problems is still challenging due to its NP-hardness. Recent efforts in data-driven methods face challenges of the need for hard-to-obtain supervision and issues with high variance in gradient estimations, leading to slow convergence and highly sub-optimal solutions. We address these issues by reformulating MTSP as a bilevel optimization problem, using the concept of imperative learning (IL). This involves introducing an allocation network that decomposes the MTSP into multiple single-agent traveling salesman problems (TSPs). The longest tour from these TSP solutions is then used to self-supervise the allocation network, resulting in a new self-supervised, bilevel, end-to-end learning framework, which we refer to as imperative MTSP (iMTSP). Additionally, to tackle the high-variance gradient issues during the optimization, we introduce a control variate-based gradient estimation algorithm. Our experiments showed that these innovative designs enable our gradient estimator to converge 20× faster than the advanced reinforcement learning baseline, and find up to 80% shorter tour length compared with Google OR-Tools MTSP solver, especially in large-scale problems (e.g. 1000 cities and 15 agents). © 2024, CC BY.

关键词： Traveling salesman problem

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