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Three-Rigid-Body-Particle Modeling and Optimization of Trajectory and Posture for Alpine Skiing

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Journal of Systems Science & Complexity 2024年第2期37卷 581-608页

作者： ZHANG Yijia FEI Qing YAO Xiaolan SUN Jian ZHANG Yanjun CHEN Zhen School of automation Beijing Institute of TechnologyBeijing 100081China

This paper presents a new study on modeling and optimization of trajectory and posture for the super-giant(SG)slalom of alpine *** is the first time that a Three-Rigid-Body-Particle model based on rigorous derivations and stability analysis is established to represent skiers trajectory and posture characteristics,as it is more accurate than the single-rigid-body model which is commonly used in existing *** addition,the Radau pseudospectral method is applied to solve the trajectory and posture optimization problem in order to obtain better skiing trajectory,skiing posture,and some key kinematic parameters of ***,this paper analyzes the effects of different body types,minimum turning radii,and flexor and extensor strength of knees and hip joint on skiing ***,based on the findings of the study,some advice about how to improve the performance of the SG slalom in view of science and technology is given to skiers and coaches for reference.

关键词： Alpine skiing modeling posture optimization Three-Rigid-Body-Particle model trajectory optimization

Attitude-adjusting dynamical behavior of cubic rover on low-gravity testbed

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Astrodynamics 2024年第1期8卷 149-159页

作者： Bowen Jiang Muhammad Talha Hussain Xiangyuan Zeng School of automation Beijing Institute of TechnologyBeijing100081China

Cubic rovers that traverse by hopping systems are promising in low-gravity *** several analyses of the control methods and mobility of the cubic rover are available,investigations of its attitude-adjusting behavior are still *** study derives the dynamic equations of the two attitude-adjusting modes of the cubic rover,referred to as walking and *** relationships between the speed threshold and rotation angle of the cubic rover were investigated in both rigid and regolith environments using a self-designed low-gravity *** studies were conducted by considering the experimental and simulated *** results of this study can be interesting for roving mission planning when exploring planetary moons and small celestial bodies.

关键词： low-gravitytestbed attitude-adjusting motion cubic rover experimental study

Coordinated Dispatch Based on Distributed Robust Optimization for Interconnected Urban Integrated Energy and Transmission Systems

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Journal of Modern Power Systems and Clean Energy 2024年第3期12卷 840-851页

作者： Wei Xu Yufeng Guo Tianhui Meng Yingwei Wang Jilai Yu the School of Electrical Engineering and automation Harbin Institute of TechnologyHarbin 150001China

To improve the economic efficiency of urban integrated energy systems(UIESs)and mitigate day-ahead dispatch uncertainty,this paper presents an interconnected UIES and transmission system(TS)model based on distributed robust ***,interconnections are established between a TS and multiple UIESs,as well as among different UIESs,each incorporating multiple energy *** Bregman alternating direction method with multipliers(BADMM)is then applied to multi-block problems,ensuring the privacy of each energy system operator(ESO).Second,robust optimization based on wind probability distribution information is implemented for each ESO to address dispatch *** column and constraint generation(C&CG)algorithm is then employed to solve the robust ***,to tackle the convergence and practicability issues overlooked in the existing studies,an external C&CG with an internal BADMM and corresponding acceleration strategy is ***,numerical results demonstrate that the adoption of the proposed model and method for absorbing wind power and managing its uncertainty results in economic benefits.

关键词： Distributed robust optimization distributionally robust dispatch urban integrated energy system transmission system external column and constraint generation(C&CG) internal Bregman alternating direction method with multipliers(BADMM)

ControlService: a containerized solution for control-algorithm-as-a-service in cloud control systems

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Science China(Information Sciences) 2024年第8期67卷 172-189页

作者： Chenggang SHAN Runze GAO Zhen YANG Wei ZHANG Yuanqing XIA School of Artificial Intelligence Zaozhuang University School of automation Beijing Institute of Technology

As an extension of networked control systems, cloud control systems(CCSs) have emerged as a new control paradigm to improve the service quality of emerging control missions, such as data-driven modeling and automated vehicles. Existing studies have used the workflow-based restructured method to optimize the computation-intensive algorithms in the CCSs. However, the challenges here are how to define and submit these algorithms' workflows as cloud services and execute these algorithms' workflows in a containerized manner. Based on these challenges, we propose a containerized solution for the control-algorithm-as-a-service(C3aS) in the CCSs, namely Control Service. It offers the control algorithm as a cloud workflow service and uses a customized workflow engine to realize the containerized execution. First, we employ a cloud workflow representation method to define a control algorithm into an abstract cloud workflow form. Afterward, we provide a cloud service representation of the abstract cloud workflow. Next, we design a workflow engine and submit the cloud service to this workflow engine to implement containerized execution of this cloud service in the CCSs. In the experiment, we discuss the cloud service form and containerized implementation of the subspace identification method. Experimental results show that the proposed Control Service has significant performance advantages in computational time, reduction percentage, and speedup ratio compared with the baseline method.

关键词： cloud control systems control-algorithm-as-a-service containerization workflow engine cloud workflow service subspace identification

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An Encode-and CRT-Based Scalability Scheme for Optimizing Transmission in Blockchain

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Computer Modeling in Engineering & Sciences 2024年第5期139卷 1733-1754页

作者： Qianqi Sun Fenhua Bai faculty of Information Engineering and automation Kunming University of Science and TechnologyKunming650500China

Blockchain technology has witnessed a burgeoning integration into diverse realms of economic and societal ***,scalability challenges,characterized by diminished broadcast efficiency,heightened communication overhead,and escalated storage costs,have significantly constrained the broad-scale application of *** paper introduces a novel Encode-and CRT-based Scalability Scheme(ECSS),meticulously refined to enhance both block broadcasting and ***,ECSS categorizes nodes into distinct domains,thereby reducing the network diameter and augmenting transmission ***,ECSS streamlines block transmission through a compact block protocol and robust RS coding,which not only reduces the size of broadcasted blocks but also ensures transmission ***,ECSS utilizes the Chinese remainder theorem,designating the block body as the compression target and mapping it to multiple modules to achieve efficient storage,thereby alleviating the storage burdens on *** evaluate ECSS’s performance,we established an experimental platformand conducted comprehensive *** results demonstrate that ECSS attains superior network scalability and stability,reducing communication overhead by an impressive 72% and total storage costs by a substantial 63.6%.

关键词： Blockchain network coding block compression transmission optimization

A model reduction approach for discrete-time linear time-variant systems with delayed inputs

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Science China(Information Sciences) 2024年第4期67卷 197-217页

作者： Ai-Guo WU Guang-Ren DUAN Yu WANG Jie ZHANG School of Mechanical Engineering and automation Harbin Institute of Technology(Shenzhen) HIT Wuhu Robot technology Research institute Center for Control Science and technology Southern University of Science and Technology

A model reduction approach is presented for discrete-time linear time-variant input-delayed systems. According to this proposed approach, a dynamical variable is constructed by taking advantage of the current state and historical information of input. It is revealed that the behavior of this dynamical variable is governed by a discrete-time linear delay-free system. It is worth noting that the presented variable transformation does not require the system matrix to be invertible. Based on the reduced delay-free models,stabilizing control laws can be easily obtained for the original delayed system. For the case with a single input delay, the constructed variable is an exact prediction for the future state, and thus the stabilizing control law could be designed by replacing the future state with its prediction. Finally, three discrete-time periodic systems with delayed input are employed to illustrate how to utilize the presented model reduction approaches.

关键词： reduction approach predictor-based feedback time-varying systems delayed input periodic system

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Autonomous multi-drone racing method based on deep reinforcement learning

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Science China(Information Sciences) 2024年第8期67卷 35-48页

作者： Yu KANG Jian DI Ming LI Yunbo ZHAO Yuhui WANG Department of automation University of Science and Technology of China institute of Advanced technology University of Science and Technology of China institute of Artificial Intelligence Hefei Comprehensive National Science Center College of automation Engineering Nanjing University of Aeronautics and Astronautics

Racing drones have attracted increasing attention due to their remarkable high speed and excellent maneuverability. However, autonomous multi-drone racing is quite difficult since it requires quick and agile flight in intricate surroundings and rich drone interaction. To address these issues, we propose a novel autonomous multi-drone racing method based on deep reinforcement learning. A new set of reward functions is proposed to make racing drones learn the racing skills of human experts. Unlike previous methods that required global information about tracks and track boundary constraints, the proposed method requires only limited localized track information within the range of its own onboard sensors. Further, the dynamic response characteristics of racing drones are incorporated into the training environment, so that the proposed method is more in line with the requirements of real drone racing scenarios. In addition, our method has a low computational cost and can meet the requirements of real-time racing. Finally, the effectiveness and superiority of the proposed method are verified by extensive comparison with the state-of-the-art methods in a series of simulations and real-world experiments.

关键词： autonomous multi-drone racing deep reinforcement learning Markov game racing drone sim-to-real

Continuous advantage learning for minimum-time trajectory planning of autonomous vehicles

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Science China(Information Sciences) 2024年第7期67卷 285-294页

作者： Zhuo LI Weiran WU Jialin WANG Gang WANG Jian SUN School of automation Beijing Institute of Technology Beijing institute of technology Chongqing Innovation Center China Academy of Launch Vehicle technology Intelligent Game and Decision Laboratory

This paper investigates the minimum-time trajectory planning problem of an autonomous vehicle. To deal with unknown and uncertain dynamics of the vehicle, the trajectory planning problem is modeled as a Markov decision process with a continuous action space. To solve it, we propose a continuous advantage learning(CAL) algorithm based on the advantage-value equation, and adopt a stochastic policy in the form of multivariate Gaussian distribution to encourage exploration. A shared actor-critic architecture is designed to simultaneously approximate the stochastic policy and the value function, which greatly reduces the computation burden compared to general actor-critic methods. Moreover, the shared actor-critic is updated with a loss function built as mean square consistency error of the advantage-value equation, and the update step is performed several times at each time step to improve data efficiency. Simulations validate the effectiveness of the proposed CAL algorithm and its better performance than the soft actor-critic algorithm.

关键词： trajectory planning continuous advantage learning stochastic policy shared actor-critic

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Distributed collaborative complete coverage path planning based on hybrid strategy

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Journal of Systems Engineering and Electronics 2024年第2期35卷 463-472页

作者： ZHANG Jia DU Xin DONG Qichen XIN Bin School of automation Beijing Institute of TechnologyBeijing 100081China National Key Laboratory of Autonomous Intelligent Unmanned Systems Beijing Institute of TechnologyBeijing 100081China

Collaborative coverage path planning(CCPP) refers to obtaining the shortest paths passing over all places except obstacles in a certain area or space. A multi-unmanned aerial vehicle(UAV) collaborative CCPP algorithm is proposed for the urban rescue search or military search in outdoor *** to flexible control of small UAVs, it can be considered that all UAVs fly at the same altitude, that is, they perform search tasks on a two-dimensional plane. Based on the agents’ motion characteristics and environmental information, a mathematical model of CCPP problem is established. The minimum time for UAVs to complete the CCPP is the objective function, and complete coverage constraint, no-fly constraint, collision avoidance constraint, and communication constraint are considered. Four motion strategies and two communication strategies are designed. Then a distributed CCPP algorithm is designed based on hybrid strategies. Simulation results compared with patternbased genetic algorithm(PBGA) and random search method show that the proposed method has stronger real-time performance and better scalability and can complete the complete CCPP task more efficiently and stably.

关键词： multi-agent cooperation unmanned aerial vehicles(UAV) distributed algorithm complete coverage path planning(CCPP)