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学者姓名：陈宇韬
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Under the dual constraints of preset time limits and coupled nonlinear dynamics, it is extremely challenging to achieve cooperative control and strong robustness guarantees for multi-agent systems. This paper focuses on the fixed-time formation control for nonholonomic wheeled mobile robots (NWMRs) via time-base generator (TBG). To begin with, distributed fixed-time formation controllers are developed to eliminate the dependence of traditional controllers on initial values. Subsequently, TBG incorporates time-dependent functions to design control strategies with either asymptotic or non-asymptotic characteristics, ensuring system convergence within a fixed time. Limiting the magnitude of control inputs not only safeguards actuators but also improves the system's robustness to external disturbances and model uncertainties. Additionally, a distributed observer based on a TBG is designed to enable each follower to estimate the state of the virtual leader within a fixed time. The observers of the followers can operate independently, eliminating the need for a global clock or precise synchronization, thereby simplifying the system design. Eventually, the effectiveness and superiority of the controller are verified by simulation. Compared with the traditional fixed-time consensus protocol, the proposed protocol reduces the amplitude of the initial linear velocity by 32.1% and the angular velocity by 32.2%. The settlement time can be preset offline, and the estimation of the settlement time is significantly more accurate.
Keyword ：
fixed-time consensus fixed-time consensus formation control formation control multiple nonholonomic wheeled mobile robots multiple nonholonomic wheeled mobile robots time-base generator time-base generator
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| GB/T 7714 | Huang, Jie , Zhao, Tingting , Lu, Wenjin et al. Practical Fixed-Time Formation Control for Wheeled Robots: An Approach Based on Time-Base Generators [J]. | INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL , 2025 . |
| MLA | Huang, Jie et al. "Practical Fixed-Time Formation Control for Wheeled Robots: An Approach Based on Time-Base Generators" . | INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL (2025) . |
| APA | Huang, Jie , Zhao, Tingting , Lu, Wenjin , Zeng, Jiazhou , Chen, Yutao . Practical Fixed-Time Formation Control for Wheeled Robots: An Approach Based on Time-Base Generators . | INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL , 2025 . |
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This paper proposes an efficient fast-optimal balanced differential game (DG) approach to address the formation control problem in dynamic environments for networked multi-agent systems (MASs). Compared to existing receding horizon distributed differential game (RH-DDG) approaches, the proposed approach employs a two-layer game structure to balance optimality and real-time performance, with a focus on formation control, collision avoidance and obstacle avoidance. In the offline layer, the problem is converted into a distributed differential game (DDG) where each agent computes strategies using distributed information from locally neighboring agents. The strategy of each agent self-enforces a unique global Nash equilibrium (G-NE) with a strongly connected communication topology, providing an optimal reference trajectory for the online game. In the online layer, a receding horizon differential game with an event-trigger mechanism (RH-DGET) is presented to track the G-NE trajectory. Ego players are triggered to update online Nash strategies only when the event-triggering condition is satisfied, ensuring the real-time safety certificate. Rigorous proofs demonstrate that the online Nash strategies converge to the offline G-NE until the trigger ends, and a certain dwell time condition is given to prevent the Zeno behavior. Simulation results validate the effectiveness of the proposed approach. © 2025 World Scientific Publishing Company.
Keyword ：
Computation theory Computation theory Game theory Game theory Multi agent systems Multi agent systems Networked control systems Networked control systems
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| GB/T 7714 | Xue, Wenyan , Huang, Jie , Chen, Nan et al. Distributed Formation Control of Multi-Agent Systems: A Novel Fast-Optimal Balanced Differential Game Approach [J]. | Unmanned Systems , 2025 , 13 (1) : 211-231 . |
| MLA | Xue, Wenyan et al. "Distributed Formation Control of Multi-Agent Systems: A Novel Fast-Optimal Balanced Differential Game Approach" . | Unmanned Systems 13 . 1 (2025) : 211-231 . |
| APA | Xue, Wenyan , Huang, Jie , Chen, Nan , Chen, Yutao , Lin, Dingci . Distributed Formation Control of Multi-Agent Systems: A Novel Fast-Optimal Balanced Differential Game Approach . | Unmanned Systems , 2025 , 13 (1) , 211-231 . |
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The concept of shared control has garnered significant attention within the realm of human-machine hybrid intelligence research. This study introduces a novel approach, specifically a dynamic control authority allocation method, for implementing shared control in autonomous vehicles. Unlike conventional mixed-initiative control techniques that blend human and vehicle inputs with weights determined by predefined index, the proposed method utilizes optimization-based techniques to obtain an optimal dynamic allocation for human and vehicle inputs that satisfies safety constraints. Specifically, a convex quadratic programm (QP) is constructed incorporating control barrier functions (CBF) for safety and control Lyapunov functions (CLF) for satisfying automated control objectives. The cost function of the QP is designed such that human weight increases with the magnitude of human input. A smooth control authority transition is obtained by optimizing over the change rate of the weight instead of the weight itself. The proposed method is verified in lane-changing scenarios with human-in-the-loop (HmIL) and hardware-in-the-loop (HdIL) experiments. Results show that the proposed method outperforms index-based control authority allocation method in terms of agility, safety and comfort.
Keyword ：
control authority allocation control authority allocation Dynamic scheduling Dynamic scheduling Human-machine systems Human-machine systems intelligent vehicle intelligent vehicle Process control Process control Real-time systems Real-time systems Resource management Resource management Safety Safety Shared control Shared control Standards Standards Vehicle dynamics Vehicle dynamics Vehicles Vehicles Wheels Wheels
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| GB/T 7714 | Chen, Yutao , Zhang, Hongliang , Chen, Haocong et al. Dynamic Control Authority Allocation in Indirect Shared Control for Steering Assistance [J]. | IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS , 2025 , 26 (3) : 3458-3470 . |
| MLA | Chen, Yutao et al. "Dynamic Control Authority Allocation in Indirect Shared Control for Steering Assistance" . | IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 26 . 3 (2025) : 3458-3470 . |
| APA | Chen, Yutao , Zhang, Hongliang , Chen, Haocong , Huang, Jie , Wang, Bin , Xiong, Zixiang et al. Dynamic Control Authority Allocation in Indirect Shared Control for Steering Assistance . | IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS , 2025 , 26 (3) , 3458-3470 . |
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Deploying wave energy converters (WECs) in an array can reduce costs due to shared infrastructure, operations, and maintenance. Nevertheless, the close placement of WEC devices introduces new challenges for control design, as interactive effects, such as radiation and diffraction, must be considered within an energy maximisation control framework to achieve optimal overall performance. Model predictive control (MPC), based on an integrated model that captures all hydrodynamic interactions, however, typically results in significant computational challenges, particularly given that many devices exhibit nonlinear hydrodynamic behaviour. To address this issue, this paper first develops a 'Neighbour-to-Neighbour (N2N)' distributed nonlinear MPC scheme, wherein the energy maximisation problem for the array is calculated distributively by the individual controllers for each WEC device. The array-level energy maximisation objective is achieved through frequent device-to-device communications. However, for certain array designs, the computational cost of the required communication may still be excessive. Therefore, we develop another 'Coordinated' distributed scheme, which incorporates an array-level coordinator into the framework, to significantly reduce the computational load associated with communication. The two schemes are benchmarked through a demonstrative numerical simulation for arrays with various numbers of devices, illustrating the necessity to account for interactive effects and verifying the efficacy of the distributed approach in retaining most of the performance, while providing advantages in computational efficiency and scalability.
Keyword ：
Arrays Arrays Coordinated control Coordinated control Distributed control Distributed control Model predictive control Model predictive control Wave energy converters Wave energy converters
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| GB/T 7714 | Chen, Yutao , Ringwood, John V. , Zhan, Siyuan . Distributed nonlinear model predictive control of an array of wave energy converters [J]. | OCEAN ENGINEERING , 2025 , 338 . |
| MLA | Chen, Yutao et al. "Distributed nonlinear model predictive control of an array of wave energy converters" . | OCEAN ENGINEERING 338 (2025) . |
| APA | Chen, Yutao , Ringwood, John V. , Zhan, Siyuan . Distributed nonlinear model predictive control of an array of wave energy converters . | OCEAN ENGINEERING , 2025 , 338 . |
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Cooperative trajectory planning of aerial-ground systems is a fundamental and challenging problem, which aims to leverage the aerial information to assist the ground tasks. Existing methods often suffer from suboptimal trajectories or computation burden. In this paper, we address cooperative trajectory planning of aerial-ground systems in which an unmanned ground vehicle (UGV) plans its local trajectory in real-time with the assistance of an unmanned aerial vehicle (UAV). Firstly, the UAV generates guidance trajectory using nonlinear model predictive control (NMPC), which considers the obstacle distribution density as a factor reflecting the coupling effect of multiple obstacles on the UGV, thereby avoiding local minima problem and improving the feasibility of the planned trajectory. Secondly, a null-space-based behavioral control (NSBC) framework is employed to merge the guidance trajectory into the UGV's own planned one as a task. Finally, an event triggering task supervisor is developed for the UGV to decide the priorities of all tasks, which reduces the switching frequency of task priorities brought by traditional rule-based task supervisors. Both simulation and experiment results show that the proposed approach has superior trajectory planning performance in terms of trajectory error, on-line computation time and the success rate of task execution.
Keyword ：
Aerial-ground systems Aerial-ground systems Behavioral control Behavioral control Model predictive control Model predictive control Trajectory planning Trajectory planning
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| GB/T 7714 | Huang, Jie , Chen, Jianfei , Zhang, Zhenyi et al. On Real-time Cooperative Trajectory Planning of Aerial-ground Systems [J]. | JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS , 2024 , 110 (1) . |
| MLA | Huang, Jie et al. "On Real-time Cooperative Trajectory Planning of Aerial-ground Systems" . | JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS 110 . 1 (2024) . |
| APA | Huang, Jie , Chen, Jianfei , Zhang, Zhenyi , Chen, Yutao , Lin, Dingci . On Real-time Cooperative Trajectory Planning of Aerial-ground Systems . | JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS , 2024 , 110 (1) . |
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Wave Energy Converters (WECs) deployed in an array can reduce investment and operational costs, such as infrastructures, operations, and maintenance. Control for WEC arrays becomes more complex due to the dynamic behaviour of individual WECs and the interactions between neighbouring devices, including their defective and radiating effects, which impact the overall system performance. This paper investigates nonlinear model predictive control (NMPC) approaches for controlling an array of wave energy converters (WECs) to extract the maximum amount of energy while respecting safety constraints. Three schemes are benchmarked, namely: (i) Centralised NMPC, where the array is considered as an augmented system; (ii) Independent NMPC, where each WEC is considered independently, neglecting all interactive effects; and (iii) Distributed NMPC (D-NMPC), where a WEC only considers the interactive effects of its nearest neighbour. The proposed approaches are demonstrated and benchmarked through comparative simulation studies based on an array of homogeneous point absorbers. Simulation results highlight the limitations of the independent and centralised approaches and reveal the potential of D-NMPC in achieving most of the performance of C-NMPC, with a computational burden similar in scale to D-NMPC.
Keyword ：
Arrays Arrays Distributed Control Distributed Control Model Predictive Control Model Predictive Control Wave Energy Converters Wave Energy Converters
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| GB/T 7714 | Zhan, Siyuan , Chen, Yutao , Lan, Jianglin et al. Energy Maximisation Control for an Array of Wave Energy Converters - A Distributed Approach [J]. | 2024 UKACC 14TH INTERNATIONAL CONFERENCE ON CONTROL, CONTROL , 2024 : 31-36 . |
| MLA | Zhan, Siyuan et al. "Energy Maximisation Control for an Array of Wave Energy Converters - A Distributed Approach" . | 2024 UKACC 14TH INTERNATIONAL CONFERENCE ON CONTROL, CONTROL (2024) : 31-36 . |
| APA | Zhan, Siyuan , Chen, Yutao , Lan, Jianglin , Zhang, Yao . Energy Maximisation Control for an Array of Wave Energy Converters - A Distributed Approach . | 2024 UKACC 14TH INTERNATIONAL CONFERENCE ON CONTROL, CONTROL , 2024 , 31-36 . |
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This paper studies control strategies of intelligent vehicles at unsignalized intersections. By considering the interaction among multiple vehicles and communication disturbances, the problem is formulated as a robust differential game in which the controlled vehicle computes actions using disturbed information of locally neighboring vehicles. Both cooperative and non-cooperative differential game models are considered. The controlled vehicle optimizes its own cost in the non-cooperative game while coordinates its strategy with other vehicles to optimize a joint cost in the cooperative game. We show that the local optimal strategy of each intelligent vehicle defined by a single optimization problem converges to global robust Nash equilibrium in the non-cooperative game, and converges to the global robust Pareto-Nash equilibrium in the cooperative game. The effectiveness of the robust differential game method is verified by simulations under two scenarios. Results show that under the proposed differential game approach, vehicles pass through unsignalized intersections more quickly than methods using traditional discrete game approaches. In addition, vehicles can avoid colliding with each other and obstacles at the presence of communication disturbances.
Keyword ：
Costs Costs differential game differential game Differential games Differential games Games Games game theory game theory Nash equilibrium Nash equilibrium Optimal control Optimal control robust Nash equilibrium robust Nash equilibrium Unsignalized intersection Unsignalized intersection Vehicle dynamics Vehicle dynamics Vehicular ad hoc networks Vehicular ad hoc networks
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| GB/T 7714 | Huang, Jie , Wu, Zhihong , Xue, Wenyan et al. Non-Cooperative and Cooperative Driving Strategies at Unsignalized Intersections: A Robust Differential Game Approach [J]. | IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS , 2024 , 25 (8) : 9535-9549 . |
| MLA | Huang, Jie et al. "Non-Cooperative and Cooperative Driving Strategies at Unsignalized Intersections: A Robust Differential Game Approach" . | IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 25 . 8 (2024) : 9535-9549 . |
| APA | Huang, Jie , Wu, Zhihong , Xue, Wenyan , Lin, Dingci , Chen, Yutao . Non-Cooperative and Cooperative Driving Strategies at Unsignalized Intersections: A Robust Differential Game Approach . | IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS , 2024 , 25 (8) , 9535-9549 . |
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Energy maximising (EM) control of wave energy converters (WECs) is a noncausal problem, where wave prediction information can be used to increase the energy conversion rate significantly. However, current approaches do not consider the prediction error evolution in the control formulation process, leading to potential unpredictable performance degradation. Moreover, most existing real-time WEC control approaches assume linear dynamics, motivated by their simplicity and mild computational cost and, thus, are not effective for real-time control for WECs with nonlinear dynamics. Targeting imperfect wave prediction and nonlinear WEC dynamics, this paper proposes a computationally-efficient nonlinear MPC (NMPC) scheme for WECs with (typically) imperfect wave excitation preview. This is achieved by introducing an input move blocking scheme when formulating and solving the online optimisation problem, i.e., defining finer discretisation grids for the control input and wave prediction at the early stages of the prediction horizon, where the wave prediction is more accurate, and coarser grids at the latter stages of the horizon, to reflect less inaccurate wave prediction information. Numerical simulation results are presented, based on a conceptual nonlinear point-absorber WEC, to verify the efficacy of the proposed NMPC method, in terms of produced energy, computational complexity, and robustness against wave prediction inaccuracy.
Keyword ：
Nonlinear model predictive control Nonlinear model predictive control Reduced computational complexity Reduced computational complexity Wave energy converter Wave energy converter Wave prediction Wave prediction
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| GB/T 7714 | Zhan, Siyuan , Chen, Yutao , Ringwood, John, V . Computationally-efficient nonlinear model predictive control of wave energy converters with imperfect wave excitation previews [J]. | OCEAN ENGINEERING , 2024 , 319 . |
| MLA | Zhan, Siyuan et al. "Computationally-efficient nonlinear model predictive control of wave energy converters with imperfect wave excitation previews" . | OCEAN ENGINEERING 319 (2024) . |
| APA | Zhan, Siyuan , Chen, Yutao , Ringwood, John, V . Computationally-efficient nonlinear model predictive control of wave energy converters with imperfect wave excitation previews . | OCEAN ENGINEERING , 2024 , 319 . |
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This paper addresses the trajectory planning and control problem of multi-spacecraft formation reconstruction in the presence of obstacles. By expressing spacecraft dynamics relative to a leader spacecraft in the formation, an integrated planning and control approach named predictive null-space-based behavior control (PNSBC) is proposed. First, a planner using null-space-based behavior control (NSBC) is designed at an upper layer to resolve multi-task conflicts. Here, both global tasks, e.g. formation keeping, and local tasks, e.g. obstacle avoidance, are considered. Second, a tracking controller is designed at the bottom layer using decentralized model predictive control. Unlike traditional two-layer approaches that treat planning and control separately, the proposed PNSBC integrates the planning and control in two ways: 1) the planner provides reference trajectories for the controller to track; 2) the model predictive control (MPC) controller provides predicted trajectories that can be employed by the planner for future task priority predictions, which extends the capability of NSBC from one-step planning to multi-step predicting. In addition, the computational burden of the MPC controller is greatly reduced by putting the nonlinear obstacle avoidance constraints into the planner as a local task. Simulation results show that such integrated approach has better performance in terms of safety constraint guarantee, fuel consumption and travel distance when compared against traditional non-integrated approaches, or all-in-one MPC methods, while constraints and task objectives are fully satisfied.& COPY; 2023 COSPAR. Published by Elsevier B.V. All rights reserved.
Keyword ：
Collision avoidance Collision avoidance Nonlinear model predictive control Nonlinear model predictive control Null-space-based behavioral control Null-space-based behavioral control Spacecraft formation Spacecraft formation
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| GB/T 7714 | Huang, Jie , Zhang, Jiancheng , Tian, Guoqing et al. Integrated planning and control for formation reconfiguration of multiple spacecrafts: A predictive behavior control approach [J]. | ADVANCES IN SPACE RESEARCH , 2023 , 72 (6) : 2007-2019 . |
| MLA | Huang, Jie et al. "Integrated planning and control for formation reconfiguration of multiple spacecrafts: A predictive behavior control approach" . | ADVANCES IN SPACE RESEARCH 72 . 6 (2023) : 2007-2019 . |
| APA | Huang, Jie , Zhang, Jiancheng , Tian, Guoqing , Chen, Yutao . Integrated planning and control for formation reconfiguration of multiple spacecrafts: A predictive behavior control approach . | ADVANCES IN SPACE RESEARCH , 2023 , 72 (6) , 2007-2019 . |
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In this work, a behavior-based adaptive dynamic programming (BADP) method is proposed for coordination control of unmanned ground vehicle-manipulator systems (UGVMs). Through a null-space-based behavioral control (NSBC) framework, the multi-objective coordination control is transformed into a single-objective tracking control at the mission layer. Since cost functions and control constraints are simplified at control layer, the complexity of controller design is reduced. Then, an identifier-actor-critic reinforcement learning algorithm framework is introduced to learn the optimal control policy by balancing the control performance and consumption. Simulation results show that control costs are reduced around 13.5% per sampling period compared to existing multiple objective control methods. Finally, the BADP method is experimentally validated using four real UGVMs.
Keyword ：
Adaptive dynamic programming Adaptive dynamic programming behavioral control behavioral control multi-objective mission multi-objective mission UGVMs UGVMs
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| GB/T 7714 | Zhang, Zhenyi , Chen, Jianfei , Mo, Zhibin et al. A Behavior-based Adaptive Dynamic Programming Method for Multiple Mobile Manipulators Coordination Control [J]. | INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS , 2023 . |
| MLA | Zhang, Zhenyi et al. "A Behavior-based Adaptive Dynamic Programming Method for Multiple Mobile Manipulators Coordination Control" . | INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS (2023) . |
| APA | Zhang, Zhenyi , Chen, Jianfei , Mo, Zhibin , Chen, Yutao , Huang, Jie . A Behavior-based Adaptive Dynamic Programming Method for Multiple Mobile Manipulators Coordination Control . | INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS , 2023 . |
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