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Coalition formation problem: a capability-centric analysis and general model

Science China(Information Sciences) 2024年第11期67卷 180-193页

作者： Jie CHEN Miao GUO Bin XIN Qing WANG Shengyu LU Yipeng WANG Yulong DING School of Automation Beijing Institute of Technology National Key Lab of Autonomous Intelligent Unmanned Systems Department of Control Science and Engineering Tongji University

Coalition formation(CF) refers to reasonably organizing robots and/or humans to form coalitions that can satisfy mission requirements, attracting more and more attention in many fields such as multirobot collaboration and human-robot collaboration. However, the analysis on CF problems remains *** provide a valuable study reference for researchers interested in CF, this paper proposed a capabilitycentric analysis of the CF problem. The key problem elements of CF are firstly extracted by referencing the concepts of the 5W1H method. That is, objects(who) form coalitions(what) to accomplish missions(why) by aggregating capabilities(how) in a specific environment(where-when). Then, a multi-view analysis of these elements and their correlation in terms of capabilities is proposed through various logic diagrams, structure charts, etc. Finally, to facilitate a deeper understanding of capability-centric CF, a general mathematical model is constructed, demonstrating how the different concepts discussed in this analysis contribute to the overall model.

关键词： coalition formation capability aggregation capability metric mission requirement environmental effect

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Toward the minimum vertex cover of complex networks using distributed potential games

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Science China(Information Sciences) 2023年第1期66卷 244-263页

作者： Jie CHEN Xiang LI Adaptive Networks and Control Lab Department of Electronic Engineering Fudan University Institute of Complex Networks and Intelligent Systems Shanghai Research Institute for Intelligent Autonomous SystemsTongji University

Vertex cover of complex networks is essentially a major combinatorial optimization problem in network science, which has wide application potentials in engineering. To optimally cover the vertices of complex networks, this paper employs a potential game for the vertex cover problem, designs a novel cost function for network vertices, and proves that the solutions to the minimum value of the potential function are the minimum vertex covering(MVC) states of a general complex network. To achieve the optimal(minimum) covering states, we propose a novel distributed time-variant binary log-linear learning algorithm,and prove that the MVC state of a general complex network is attained under the proposed optimization algorithm. Furthermore, we estimate the upper bound of the convergence rate of the proposed algorithm,and show its effectiveness and superiority using numerical examples with representative complex networks and optimization algorithms.

关键词： minimum vertex cover Nash equilibrium convergence rate scale-free network random graph

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Modified Covariance Intersection-Based Sensor Fault Tolerance of a Gas Turbine Engine

Modified Covariance Intersection-Based Sensor Fault Toleranc...

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AIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Chakraborty, Tirthankar Maity, Arnab Intelligent Systems and Control Lab Department of Aerospace Engineering Indian Institute of Technology Bombay Mumbai400076 India

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

Fault tolerance is crucial in the design and operation of gas turbine engines, where even minor malfunctions can disrupt operations and compromise performance. This paper presents a modified covariance intersection-based decentralized estimator which can ensure uninterrupted operation amidst sensor failures. A network of sensor nodes within the engine is considered. Each node in the network computes a local state estimate, which is subsequently fused with the other node estimates at each time instant. The developed algorithm uses a novel weight adaptation scheme to fuse the node estimates and the associated covariances. The node weights are expressed as a function of the covariance matrix of the node estimate and a scaling matrix. This algorithm is tested through simulation by injecting faults in the sensors of a small-scale gas turbine engine primarily used for research, called the SR-30 engine. The simulation results illustrate the effectiveness of the proposed estimator in ensuring the integrity of the state estimates in the presence of drift and bias faults in the sensors. © 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Gas turbines

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Nested Sliding Mode control Based Impact Angle Guidance with Bounded Input

Nested Sliding Mode Control Based Impact Angle Guidance with...

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AIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Surve, Prajakta Kumar, Shashi Ranjan Intelligent Systems & Control Lab Department of Aerospace Engineering Indian Institute of Technology Bombay Powai Mumbai400076 India

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

In this paper, a nonlinear guidance law for impact angle-constrained interception of nonmaneuvering targets, respecting the bounds on the control input - the commanded interceptor lateral acceleration, is proposed. By modeling the required interceptor lateral acceleration as a first-order dynamics, which is a function of the maximum permissible value of control input and guidance command, the control input is maintained within the predefined bounds. The dynamics is chosen in such a way that the resulting input will never violate the prescribed bounds. To design the guidance command, also known as commanded lateral acceleration, we employ a sliding surface based on the error between actual and desired line-of-sight (LOS) angles and the LOS rate, facilitating a collision course with zero miss distance. A secondary sliding surface is designed as a function of the primary sliding surface and its rate. This sliding surface enables the control over the required interceptor lateral acceleration. An effective guidance command for precise interception at given impact angle, considering the bounds on control input, is then derived using the sliding mode control technique. Numerical simulations validate the merits and claims of the presented guidance approach. © 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Sliding mode control

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Adaptive Unscented Kalman Filter Based Sensor Fusion for Aircraft Positioning Relative to Unknown Runway

Adaptive Unscented Kalman Filter Based Sensor Fusion for Air...

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AIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Ghosh, Nabarun Maity, Arnab Intelligent Systems and Control Lab Department of Aerospace Engineering Indian Institute of Technology Bombay Maharashtra Mumbai400076 India

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

This paper proposes an estimator to provide precise position, velocity, and orientation for a landing aircraft relative to the runway based on image sensors, IMU sensor data, and barometric sensor measurements. This work excludes GPS data, as it is expected that the proposed estimator can be used for fault detection in GPS and instrument landing systems. The runway is unknown, and hence, its width is estimated online. An adaptive UKF-based approach is adopted to estimate the states. In order to verify the nearer-to-practical performance and accuracy of bias estimation, realistically simulated data that constitute noises and biases from the sensors are taken into consideration. The proposed approach provides a solution for nonlinear state estimation in the presence of measurement noises that are non-additive. In addition to this, it provides estimates of the unknown measurement noise covariance. A comparative study is conducted between the conventional UKF and the proposed AUKF to analyze the adopted approach. Results show that the proposed algorithm gives comparable estimation results and faster convergence than the conventional UKF. © 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Fault detection

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Event-triggered consensus control of heterogeneous multi-agent systems: model-and data-based approaches

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Science China(Information Sciences) 2023年第9期66卷 151-167页

作者： Xin WANG Jian SUN Fang DENG Gang WANG Jie CHEN School of Automation Beijing Institute of Technology National Key Lab of Autonomous Intelligent Unmanned Systems Beijing Institute of Technology Chongqing Innovation Center Department of Control Science and Engineering Tongji University

This article addresses the model-and data-based event-triggered consensus of heterogeneous leader/follower multi-agent systems(MASs). A dynamic periodic transmission protocol is developed to alleviate the communication and computational burden, where the followers can interact locally with neighbors to approach the dynamics of the leader. Capitalizing on a discrete-time looped-functional, a model-based consensus condition for the closed-loop MASs is derived as linear matrix inequalities(LMIs), along with a design method for obtaining distributed event-triggered controllers and the associated triggering *** collecting noise-corrupted state-input measurements in offline open-loop experiments, a data-based leader/follower MAS representation is derived and employed to address the data-driven consensus control problem without explicit MAS models. This result is subsequently generalized to guarantee an H∞-consensus control performance. Finally, a simulation example is given to corroborate the efficiency of the proposed distributed triggering scheme and the data-driven consensus controller.

关键词： data-driven control multi-agent system consensus looped-functional LMI

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An adaptive large neighborhood search for the multi-point dynamic aggregation problem

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control Theory and Technology 2024年第3期22卷 360-378页

作者： Shengyu Lu Bin Xin Jie Chen Miao Guo School of Automation Beijing Institute of TechnologyBeijing 100081China National Key Lab of Autonomous Intelligent Unmanned Systems Beijing 100081China Department of Control Science and Engineering Tongji UniversityShanghai 201804China

The multi-point dynamic aggregation(MPDA)problem is a challenging real-world *** the MPDA problem,the demands of tasks keep changing with their inherent incremental rates,while a heterogeneous robot fleet is required to travel between these tasks to change the time-varying state of each *** robots are allowed to collaborate on the same task or work separately until all tasks are *** is challenging to generate an effective task execution plan due to the tight coupling between robots abilities and tasks'incremental rates,and the complexity of robot *** effectiveness consideration,we use the variable length encoding to avoid redundancy in the solution *** creatively use the adaptive large neighborhood search(ALNS)framework to solve the MPDA *** the proposed algorithm,high-quality initial solutions are generated through multiple problem-specific solution construction *** heuristics are also used to fix the broken solution in the novel integrated decoding-construction repair process of the ALNS *** results of statistical analysis by the Wilcoxon rank-sum test demonstrate that the proposed ALNS can obtain better task execution plans than some state-of-the-art algorithms in most MPDA instances.

关键词： Adaptive large neighborhood search(ALNS) Multi-point dynamic aggregation(MPDA) Heuristic solution construction Multi-robot collaboration

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Mean policy-based proximal policy optimization for maneuvering decision in multi-UAV air combat

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Neural Computing and Applications 2024年第31期36卷 19667-19690页

作者： Zheng, Yifan Xin, Bin He, Bin Ding, Yulong Department of Control Science and Engineering Tongji University Shanghai China Frontiers Science Center for Intelligent Autonomous Systems Ministry of Education Shanghai China School of Automation Beijing Institute of Technology Beijing China National Key Lab of Autonomous Intelligent Unmanned Systems Beijing China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Beijing China

Autonomous maneuvering decision-making is a crucial technology for Unmanned Aerial Vehicles (UAVs) to take the air domination in modern unmanned warfare. With the advantage of balancing exploration and exploitation, as well as the immediacy of end-to-end output by combining with deep neural network, multi-agent reinforcement learning (MARL) has made remarkable achievements in multi-UAV autonomous air combat maneuvering decision-making (MUAAMD). However, the implementation of effective cooperative policy learning remains a challenging issue for MARL methods with centralized training decentralized execution (CTDE) paradigm. This paper proposes a MARL-based method to improve the performance of cooperation in MUAAMD. Firstly, considering the constraints of dynamic and limited perception for UAVs in the realistic air combat scenario, the MUAAMD problem is formulated based on partially observable Markov game (POMG) model. Secondly, a novel efficient MARL algorithm named the mean policy-based proximal policy optimization (MP3O) is introduced. Specifically, a joint policy optimization mechanism is constructed by estimating the policies of neighboring agents in group as a mean-field approximation while training, which enables both centralized evaluation and improvement of cooperative policy under the CTDE paradigm. Thirdly, by combining with three improvement techniques, a cooperative decision-making framework for MUAAMD based on MP3O is proposed. Empirically, results of simulations and comparative experiments validate the effectiveness of proposed method in promoting cooperative policy learning in resolving MUAAMD problem. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Decision making

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Data-driven consensus control of fully distributed event-triggered multi-agent systems

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Science China(Information Sciences) 2023年第5期66卷 147-161页

作者： Yifei LI Xin WANG Jian SUN Gang WANG Jie CHEN School of Automation Beijing Institute of Technology The State Key Lab of Autonomous Intelligent Unmanned Systems Beijing Institute of Technology Beijing Institute of Technology Chongqing Innovation Center Department of Control Science and Engineering Tongji University

This study investigates the consensus control issue in discrete-time linear multi-agent systems(MASs) using data-driven control under undirected communication networks. To alleviate the communication burden, an adaptive event-triggered control strategy involving only local information is proposed and a model-based stability condition is derived that guarantees the asymptotic consensus of MASs. Furthermore,a data-based consensus condition for unknown MASs is established by combining a data-based system representation with the model-based stability condition, using only pre-collected noisy input-state data instead of the accurate system information a priori. Specifically, both model-based and data-driven event-triggered controllers can be utilized without requiring any global information. The validity and correctness of the controllers and associated theoretical results are demonstrated via numerical simulations.

关键词： distributed control event-triggered control data-driven control discrete-time MASs

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Detachment Behavior of Gecko Toe in Functional Strategies for Bionic Toe

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Journal of Bionic engineering 2024年第2期21卷 707-717页

作者： Qingfei Han Wei Wang Huan Shen Xincheng Feng Haoran Zhang Qian Li Yi Sun Huapeng Wu Aihong Ji Lab of Locomotion Bioinspiration and Intelligent Robots College of Mechanical and Electrical EngineeringNanjing University of Aeronautics and AstronauticsNanjing210016China Laboratory of Intelligent Machines School of Energy SystemsLappeenranta-Lahti University of Technology53850LappeenrantaFinland State Key Laboratory of Mechanics and Control for Aerospace Structures Nanjing University of Aeronautics and AstronauticsNanjing210016China

Geckos can efficiently navigate complex terrains due to their multi-level adhesive system that is present on their *** setae are responsible for the gecko’s extraordinary adhesion and have garnered wide attention from the scientific *** majority of the reported works in the literature that have dealt with the peeling models mainly focus on the gecko hierarchical adhesive system,with limited attention given to investigating the influence of gecko toe structure on the *** these lines,to gain a deeper understanding of the rapid and effortless detachment abilities of gecko toes,the peeling behavior of gecko toes on vertical surfaces was primarily investigated in this *** specifically,the detachment time of a single toe on a smooth acrylic plate was measured to be 0.41±0.21 ***,it was observed that the toe assumed a"U"-shaped structure upon complete ***,Finite Element Analysis(FEA)models for three different types of gecko toes were developed to simulate both the displacement-peel and the moment-peel *** the segmentation of the adhesive layer led to a gradual decrease in the resultant force,as well as the normal and tangential ***,a gecko-inspired toe model was constructed and powered by Shape Memory Alloy(SMA).A systematic comparison between the vertical drag separation and the outward flip separation was also *** our analysis,it was clearly demonstrated that outward peel separation significantly necessitated the reduction of the peeling force,thus confirming the advantageous nature of the outward motion in gecko toe *** data not only contribute to a deeper understanding of the gecko detachment behavior but also offer valuable insights for the advancement of the wall-climbing robot feet.

关键词： Gecko toes Detachment behavior Finite element analysis Gecko-inspired toe

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