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Dynamic Tip-Over Avoidance Method for Mobile Manipulators Based on the Extended Zero-Moment Point Algorithm for Human–Robot Collaboration

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Journal of Computing and Information Science in engineering 2025年第5期25卷 051003页

作者： Tao, Yong Liu, Haitao Song, Yian Deng, Changyi Wang, Baicun Zheng, Pai School of Mechanical Engineering and Automation Beihang University Beijing 100191 China Institute of Software China Industrial Control Systems Cyber Emergency Response Team Beijing 100040 China School of Mechanical Engineering Zhejiang University Hangzhou 310030 China Research Institute for Advanced Manufacturing Department of Industrial and Systems Engineering The Hong Kong Polytechnic University Hung Hom Hong Kong

Human–robot collaboration (HRC), as an important role in intelligent manufacturing, is widely utilized in modern factories. Mobile manipulators offer greater flexibility due to the ability to simultaneously move their bases and arms. This provides them an advantage in facing challenging tasks such as flexible production and intelligent manufacturing. The environment of modern factories is complex, with slopes and thresholds at the entrance. Stability plays a fundamental role in complex environments. Therefore, for the future deployment and application of mobile manipulator in HRC, a novel dynamic tip-over avoidance method is proposed for mobile manipulators based on the extended zero-moment point (ZMP) algorithm. This method extends the traditional ZMP stability criterion into three dimensions, deriving a system-wide three-dimensional (3D) zero-moment point. The integration of the extended ZMP with redundant features facilitates adaptive weight matrix adjustments, enabling the robot to adapt its motion based on environmental constraints, thus preventing instability such as tip-over. Simulation verification is carried out withcoppeliasim. Experimental verification is performed using the MR2000 + FR3 mobile manipulator. The results confirm that the extended ZMP algorithm effectively prevents tipping in complex environments.

关键词： tip-over avoidance null-space projection Weight (Mass) mobile manipulator Stability Manipulators Robots human–robot interfaces/interactions velocity controlled manufacturing automation extended ZMP Algorithms

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Multi-objective Optimization of Production Scheduling Using Particle Swarm Optimization Algorithm for Hybrid Renewable Power Plants with Battery Energy Storage System

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Journal of Modern Power Systems and Clean Energy 2021年第2期9卷 285-294页

作者： Jon Martinez-Rico Ekaitz Zulueta Ismael Ruiz de Argandona Unai Femandez-Gamiz Mikel Armendia The Automation and Control Unit Fundacion TeknikerBasque Research and Technology Alliance(BRTA)Ifiaki Goenaga520600 the University of the Basque Country Ing.Torres Quevedo148013 BilbaoSpain the Department of Systems Engineering and Control College of Engineering at Vitoria-GasteizUniversity of the Basque CountryNieves Cano1201006 Vitoria-GasteizSpain the Department of Nuclear and Fluid Mechanics College of Engineering at Vitoria-GasteizUniversity of the Basque CountryNieves Cano1201006 Vitoria-GasteizSpain

Considering the increasing integration of renewable energies into the power grid,batteries are expected to play a key role in the challenge of compensating the stochastic and intermittent nature of these energy ***,the deployment of batteries can increase the benefits of a renewable power *** way to increase the profits with batteries studied in this paper is performing energy *** strategy is based on storing energy at low electricity price moments and selling it when electricity price is *** this paper,a hybrid renewable energy system consisting of wind and solar power with batteries is studied,and an optimization process is conducted in order to maximize the benefits regarding the dayahead production scheduling of the plant.A multi-objective cost function is proposed,which,on the one hand,maximizes the obtained profit,and,on the other hand,reduces the loss of value of the battery.A particle swarm optimization algorithm is developed and fitted in order to solve this non-linear multi-objective *** the aim of analyzing the importance of considering both the energy efficiency of the battery and its loss of value,two more simplified cost functions are *** show the importance of including the energy efficiency in the cost function to ***,it is proven that the battery lifetime increases substantially by using the multi-objective cost function,whereas the profitability is similar to the one obtained in case the loss of value is not ***,due to the small difference in price among hours in the analyzed Iberian electricity market,it is observed that low profits can be provided to the plant by using batteries just for arbitrage purposes in the day-ahead market.

关键词： Battery energy storage system energy arbitrage hybrid renewable energy system particle swarm optimization

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Aggressive Trajectory Generation for a Swarm of Autonomous Racing Drones

Aggressive Trajectory Generation for a Swarm of Autonomous R...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Yuyang Shen Jin Zhou Danzhe Xu Fangguo Zhao Jinming Xu Jiming Chen Shuo Li College of Control Science and Engineering Zhejiang University Hangzhou China Department of Automation Zhejiang University of Technology Hangzhou China School of Automation Northwestern Polytechnical University Xi'an China

Autonomous drone racing is becoming an excellent platform to challenge quadrotors' autonomy techniques including planning, navigation and control technologies. However, most research on this topic mainly focuses on single drone scenarios. In this paper, we describe a novel time-optimal trajectory generation method for generating time-optimal trajectories for a swarm of quadrotors to fly through pre-defined waypoints with their maximum maneuverability without collision. We verify the method in the Gazebo simulations where a swarm of 5 quadrotors can fly through a complex 6-waypoint racing track in a $35m\times 35m$ space with a top speed of 14m/s. Flight tests are performed on two quadrotors passing through 3 waypoints in a $4m\times 2m$ flight arena to demonstrate the feasibility of the proposed method in the real world. Both simulations and real-world flight tests show that the proposed method can generate the optimal aggressive trajectories for a swarm of autonomous racing drones. The method can also be easily transferred to other types of robot swarms.

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Texture Analysis of Breast US Images Using Morphological Transforms, Hausdorff Dimension and Bagging Ensemble Method

Texture Analysis of Breast US Images Using Morphological Tra...

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Mediterranean Conference on control and automation (MED)

作者： Gigi Tăbăcaru Simona Moldovanu Marian Barbu Department of Automatic Control and Electrical Engineering Faculty of Automation Computers Electrical Engineering and Electronics “Dunarea de Jos” University of Galati Romania Computer Science and Information Technology Faculty of Automation Computers Electrical Engineering and Electronics “Dunarea de Jos” University of Galati The Modelling & Simulation Laboratory Dunarea de Jos University of Galati Galati Romania

ISBN: (数字)9798350395440

ISBN: (纸本)9798350395457

In this work, an attempt is made for the first time to use the measurement pattern generated by morphological transformation quantified by Hausdorff fractal dimension (HFD) and classified with ensemble learning based on bagging. The proposed work uses three morphological transformations for image preprocessing: hit-and-miss transform (HMT), white (WHT), and black top-hat (BHT). The pattern texture of US breast images is described by extracting the HFD from the regions of interest (ROI) after the ultrasound (US) images have been preprocessed. The main objective of this study was achieved by comparatively analyzing the classification performance of features using the Random Forest (RF), Extra Trees (ET) classifier, and bagging ensemble method based on XGBoot classifier. In presented study, the XGBoost classifier and BHT image processing method give an accuracy of 89.8% in a binary classification, benign versus malignant breast cancer.

关键词： Ultrasonic imaging Transforms Feature extraction Time measurement Fractals Ensemble learning Image preprocessing

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Fixed-time extended state observer-based trajectory tracking control for autonomous underwater vehicles

Fixed-time extended state observer-based trajectory tracking...

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作者： Zheng, Jiaqi Song, Lei Liu, Lingya Yu, Wenbin Zhu, Shanying Wang, Yiyin Chen, Cailian Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai China

In this paper, we investigate the trajectory tracking control problem for autonomous underwater vehicles (AUVs) with time-varying external disturbances of currents and waves in the sea. To solve the problem, a fixed-time extended state observer (FTESO)-based tracking controller is proposed. Firstly, by using the extended state observer, the FTESO is proposed for estimating the external disturbances and the velocities of the AUV within the fixed convergence time. Based on the FTESO, the fixed-time controller is proposed for reducing the tracking errors and improving robustness performance. Theoretical analysis is given, which shows that the unknown external disturbances can be compensated and tracking error can converge to zero within the fixed time. Simulation results show that the proposed FTESO controller not only guarantees the fixed-time convergence but also reduces the trajectory tracking errors of the AUV. © 2021 Chinese Automatic control Society and John Wiley & Sons Australia, Ltd.

关键词： Autonomous underwater vehicles

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Disturbance Observer Based on Terminal Sliding-Mode control for a Secure Communication of Fractional-Order Takagi-Sugeno Fuzzy Chaotic Systems

Disturbance Observer Based on Terminal Sliding-Mode Control ...

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International Conference on Advanced Mechanical engineering, automation and Sustainable Development, AMAS 2021

作者： Giap, Van Nam Nguyen, Quang Dich Trung, Nguyen Kien Huang, Shyh-Chour Trinh, Xuan Thang Institute for Control Engineering and Automation Hanoi University of Science and Technology Hanoi100000 Viet Nam School of Electrical Engineering Hanoi University of Science and Technology Hanoi100000 Viet Nam Department of Mechanical Engineering National Kaohsiung University of Science and Technology Kaohsiung80778 Taiwan Faculty of Mechanical Engineering Hung Yen University of Technology and Education Hung Yen160000 Viet Nam

ISBN: (纸本)9783030996659

In this study, the disturbance observer (DOB) for a secure communication system (SCS) of the fractional-order (FO) Takagi-Sugeno (T-S) fuzzy systems was newly proposed. The synchronization of the master and slave systems (MSS) was guaranteed by a terminal sliding mode control (TSMC) method. The experimental study of computer communication-based MATLAB software with support of FOMCON toolbox was used to confirm the correction of the proposed theories. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Disturbance observer Fractional order Secure communication T-S fuzzy chaotic system Terminal sliding mode control

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Exploring the Economic Feasibility of Advanced Air Mobility in the Early Stages

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年第5期9卷 4826-4830页

作者： Jingqiu Guo Long Chen Lingxi Li Xiaoxiang Na Ljubo Vlacic Fei-Yue Wang Key Laboratory of Road and Traffic Engineering of the Ministry of Education Tongji University Shanghai China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Department of Electrical and Computer Engineering Purdue School of Engineering and Technology Indiana University–Purdue University Indianapolis (IUPUI) Indianapolis IN USA Department of Engineering University of Cambridge Cambridge U.K. Institute of Intelligent and Integrated Systems and the School of Engineering and Built Environment Griffith University Nathan QLD Australia State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Institute of Engineering Macau University of Science and Technology Macau China

Advanced Air Mobility (AAM) envisages a sustainable, safe, convenient, and affordable air transport system. In socio-technical transition of AAM, there are a number of trade-offs in ecosystem that need to be studied. Three perspectives on economic feasibility are explored: first, based on history of VTOL services and value of time estimates, we discuss whether AAM can provide customers with competitive mobility services; second, what are the stakeholders’ insights on the deployment of AAM; last, the experience in the development of autonomous driving technology, such as parallel intelligence, can inform future AAM research.

关键词： Active appearance model Costs Economics Transportation Helicopters Aircraft propulsion Public transportation

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Design and application of a one-stop mobile application sharing platform for steel enterprises

Design and application of a one-stop mobile application shar...

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第42届中国控制会议

作者： Xinzhe Chen Luefeng Chen Jie Hu Qingfeng Yang Min Wu Witold Pedrycz School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Department of Electrical and Computer Engineering University of Alberta

As China's steel production accounts for an increasing share of the world's output, the intelligent transformation of the steel industry is becoming increasingly urgent. To address issues such as low levels of mobile informationization in steel enterprises and the lack of an industry-specific mobile application platform, it is of great significance to establish a shared mobile application platform for the steel industry. In this paper, the requirements of the platform were analyzed, and the platform's functions were designed. The software design of the platform was then carried out, and the entire mobile application sharing platform was developed, effectively improving the production management efficiency of steel enterprises. The results indicate that the platform can effectively meet the needs of steel enterprises and has significant engineering significance.

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Computationally Efficient VBR-Based Sensitivity Analysis of Induction Motors

Computationally Efficient VBR-Based Sensitivity Analysis of ...

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IEEE Energy Conversion Congress and Exposition, ECCE

作者： Hossein Nejadi Koti Zahra Valipoor Nabeel A. O. Demerdash Motion Control Team Rockwell Automation Inc. Mequon USA Engineering Department Electrical and Computer Marquette University Milwaukee USA

Sensitivity analysis is a powerful tool that can be utilized for reducing the size of the design space at hand to explore and significantly reduce the computational burden of the optimization process. This is achieved by "smart" design variable selection. The term "smart" indicates fixing the un-conflicting design variables that do not require exploration to their maximum or minimum values, depending on their enhancing or degrading effect on the objective functions and allowing the conflicting design variables to be explored within their allowable dynamic range. Intelligent optimization is a critical part of induction motor design process. In this paper, computationally efficient sensitivity analysis is performed to effectively reduce the number of the design variables that will be actively explored in the optimization process of the induction motors. This goal is achieved through the VBR-based TS-FEA together with Design of Experiment and Response Surface Methodology. In addition, the motor estimated losses, including the calculated core losses are fed to a thermal network model to estimate the temperature of different motor components.

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Domain-adaptation with knowledge accumulation through parallel stacked autoencoders: methodology and application to sulfur recovery

Domain-adaptation with knowledge accumulation through parall...

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American control Conference (ACC)

作者： Tianhao Mou Jinfeng Liu Yuanyuan Zou Shaoyuan Li Maria Gabriella Xibilia Department of Automation Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Jiao Tong University Shanghai China Department of Chemical and Materials Engineering University of Al-berta Edmonton Alberta Canada Department of Engineering University of Messina Messina Italy

ISBN: (数字)9798350382655

ISBN: (纸本)9798350382662

Data-driven predictive models for end-point quality variables are important tools in industrial process modeling. However, establishing an effective predictive model with limited labeled data remains challenging. Transfer learning (TL) offers a solution by leveraging knowledge from similar but different tasks. This paper introduces a novel TL-based predictive model, domain-adaptation parallel stacked auto encoders (DA-PSAE), which can extract and accumulate knowledge from multiple similar processes. First, a parallel model structure is designed for the simultaneous extraction of static and plastic latent features. Besides, an effective TL-based training strategy is proposed, which utilizes data from multiple similar processes. The proposed model is applied to a sulfur recovery unit composed of four parallel sub-units. Experimental results verify the effectiveness of the proposed model.

关键词： Training Industries Process modeling Transfer learning Predictive models Feature extraction Data models

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