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40th Chinese control Conference (CCC)

作者： Wang, Luxiang Liu, Xiaoyang Hu, Yuanfa Hu, Xiaoting Jiangsu Normal Univ Sch Comp Sci & Technol Xuzhou 221116 Jiangsu Peoples R China

ISBN: (纸本)9789881563804

This paper considers the predefined-time containment control (PTCC) of second-order nonlinear multi-agent systems with external disturbances. Firstly, a new terminal sliding mode surface is developed to ensure the predefined-time system convergence along the sliding mode surface. Secondly, a terminal sliding mode controller is correspondingly designed to achieve the predefined-time containment control. It is shown that the obtained control time is irrespective of any control parameters or any initial values. Finally, one simulation example is proposed to show the effectiveness of the designed protocols.

关键词： predefined-time control Containment control Multi-agent systems External disturbances Sliding mode control

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predefined-time Containment control for Nonlinear Multi-agent Systems via Sliding Mode control

Predefined-Time Containment Control for Nonlinear Multi-agen...

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第40届中国控制会议

作者： Luxiang Wang Xiaoyang Liu Yuanfa Hu Xiaoting Hu School of Computer Science and Technology Jiangsu Normal University

This paper considers the predefined-time containment control(PTCC) of second-order nonlinear multi-agent systems with external disturbances. Firstly, a new terminal sliding mode surface is developed to ensure the predefined-time system convergence along the sliding mode surface. Secondly, a terminal sliding mode controller is correspondingly designed to achieve the predefined-time containment control. It is shown that the obtained control time is irrespective of any control parameters or any initial values. Finally, one simulation example is proposed to show the effectiveness of the designed protocols.

关键词： predefined-time control Containment control Multi-agent systems External disturbances Sliding mode control

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Adaptive predefined-time specific performance control for underactuated multi-AUVs: An edge computing-based optimized RL method

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OCEAN ENGINEERING 2025年 318卷

作者： Liu, Haitao Feng, Zhijian Tian, Xuehong Mai, Qingqun Guangdong Ocean Univ Sch Mech Engn Zhanjiang 524088 Peoples R China Guangdong Ocean Univ Shenzhen Inst Shenzhen 518120 Peoples R China Guangdong Engn Technol Res Ctr Ocean Equipment & M Zhanjiang 524088 Peoples R China

In this paper, an optimal control strategy with predefined time-adaptive dynamic programming with a dual-layer structure consisting of a trajectory analysis rule layer and an optimal control rule layer is proposed for solving the 3D trajectory tracking problem of underactuated multi-UAV formation control. In the trajectory analysis layer, an edge computing-based event-triggered fully distributed adaptive state compensator is developed, which is utilized to estimate the state information of the virtual leader to optimize the consistency problem of formation control. In addition, event triggering via edge computing reduces the communication burden. In the optimal control rule layer, to overcome the complexity of the gradient descent algorithm of reinforcement learning (RL) via the square of the HJB equation, first, the solution via a positive function, which is equivalent to the HJB equation, is derived to reduce the complexity of the algorithm. Then, the optimized reinforcement actor-critic neural network (NN) structure is combined with dynamic planning to ensure that each subsystem can achieve the optimal solution. A full-state constraint is imposed on the error system to increase the convergence speed and accuracy of the control system, and a new boundary performance function is designed to address its brittleness to increase the system's ability to cope with unexpected situations. The convergence of all the signals at a globally predefined time is theoretically proven, whereas the effectiveness of the control system is demonstrated via experimental simulations.

关键词： Reinforcement learning predefined-time control Edge computing Flexibility performance function Underactuated AUV

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predefined-time nearly optimal trajectory tracking control for autonomous surface vehicles with unknown dynamics

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OCEAN ENGINEERING 2025年 327卷

作者： Wu, Ting Zhang, Yan Yang, Xiaofei Ye, Hui Xiang, Zhengrong Nanjing Univ Sci & Technol Sch Automat Nanjing 210094 Jiangsu Peoples R China Jiangsu Univ Sci & Technol Sch Automat Zhenjiang 215100 Jiangsu Peoples R China

This paper investigates the predefined-time nearly optimal trajectory tracking control for autonomous surface vehicles (ASVs) with unknown dynamics. Unlike the existing methods, which only ensure asymptotic or finite-time stability, the proposed control method allows users to specify the settling time and convergence accuracy. Firstly, a performance index function that measures tracking error costs and control input energy costs is presented. Due to the difficulty in solving the Hamilton-Jacobi-Bellman (HJB) equation, a nearly optimal method via reinforcement learning (RL) within the identifier-actor-critic architecture is proposed. Meanwhile, an improved piecewise function including settling time and convergence accuracy is constructed. This piecewise function is embedded into the approximate optimal performance index function and control input, which avoids the chattering and singularity phenomena in the sign function. The control scheme approximates the optimal value function, control policy, and unknown dynamics without relying on the precise knowledge of system dynamics and ensures that tracking errors converge to a specific accuracy within a predefined time. Finally, simulation results demonstrate the effectiveness of the proposed control method.

关键词： predefined-time control Autonomous surface vehicle Nearly optimal control Trajectory tracking control Reinforcement learning Identifier-actor-critic architecture

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Enhanced predefined-time Tracking and Synchronization control for Multimotor Servo Systems

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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2025年第7期72卷 7094-7105页

作者： Song, Jiangchao Ren, Xuemei Na, Jing Gong, Jianning Zheng, Dongdong Beijing Inst Technol Sch Automat Beijing 100081 Peoples R China Kunming Univ Sci & Technol Fac Elect & Mech Engn Kunming 650500 Peoples R China Kunming Univ Sci & Technol Yunnan Key Lab Intelligent Control & Applicat Kunming 650500 Peoples R China China Acad Machinery Sci & Technol Beijing 100044 Peoples R China

An enhanced predefined-time control strategy is proposed to achieve load tracking and motor synchronization for multimotor servo systems. A new sufficient condition of the Lyapunov function is established to guarantee both predefined-time stability and practical predefined-time stability, which results in a smaller convergence domain. Based on this condition, we develop a predefined-time sliding mode tracking controller that ensures the convergence of the tracking error between the load output and the desired trajectory. This controller exhibits predefined-time convergence capabilities in both the reaching and sliding mode phases. To solve the synchronization problem between motors, a novel predefined-time synchronization controller is proposed within the mean relative coupling control framework, ensuring rapid consistency of motor speeds. The convergence time for both the tracking error and the synchronization error is predefined based on practical requirements. The stability of the proposed control method is guaranteed by Lyapunov theory. Furthermore, numerical simulations and experiments are conducted, and performance indicators are used to quantitatively analyze the results, thereby demonstrating the effectiveness of the proposed method.

关键词： Multimotor servo systems predefined-time control synchronization control tracking control Multimotor servo systems predefined-time control synchronization control tracking control

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predefined-time robust attitude tracking control of flexible spacecraft with continuous and nonsingular performance

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AEROSPACE SCIENCE AND TECHNOLOGY 2025年 159卷

作者： Xiao, Yan Wang, Yunteng Ye, Dong Sun, Zhaowei Harbin Inst Technol State Key Lab Microspacecraft Rapid Design & Intel Harbin 150001 Peoples R China

To address the predefined-time robust attitude tracking control of flexible spacecraft with both external disturbances and model uncertainties, this paper proposes an adaptive terminal sliding mode controller. A modal observer is designed to estimate the unmeasured modal information of flexible attachments, and the estimation error is regarded as a part of the lumped disturbance. The term with a power index less than one in the terminal sliding mode is replaced by a piecewise function such that the controller is global nonsingular. To ensure the continuity of the applied control torque to avoid chattering phenomenon, the signum function in the robust term is replaced by the hyperbolic tangent function and its influence on control accuracy is analyzed quantitatively. The Lyapunov stability analysis shows that the attitude tracking error can be drawn into a small neighborhood near zero before the specified time which can be easily adjusted during the controller design without initial conditions constraint. Finally, we evaluate the predefined-time convergence performance by numerical simulations.

关键词： Flexible spacecraft Attitude tracking control predefined-time control Modal observer Terminal sliding mode

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Distributed predefined-time neural adaptive control design for consensus of networked Euler-Lagrange systems

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INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE 2025年第5期56卷 1130-1142页

作者： Yao, Qijia Li, Qing Jahanshahi, Hadi Univ Sci & Technol Beijing Sch Automat & Elect Engn Beijing 100083 Peoples R China Univ Sci & Technol Beijing Key Lab Knowledge Automat Ind Proc Minist Educ Beijing 100083 Peoples R China Inst Elect & Elect Engineers Toronto ON Canada

This article presents a distributed predefined-time neural adaptive control scheme for the consensus of networked Euler-Lagrange (EL) systems under model uncertainties and external perturbations through directed communication topology. First, a distributed predefined-time observer is constructed to estimate the leader's state information for each follower agent. Then, based on the recovered information, the predefined-time local controller is designed for each follower agent by utilising the predefined-time backstepping control approach. Moreover, the neural network (NN) is incorporated to identify the lumped unknown item. Particularly, an indirect learning mechanism is adopted to determine the upper bound of the optimal NN weight. In this way, the computational cost of the presented controller is greatly degraded. Stability evaluation shows that the presented controller can guarantee the position and velocity synchronisation errors regulate to the minor regions around zero in predefined time. Lastly, simulated studies are conducted on the consensus of networked robotic manipulators to validate the obtained results.

关键词： Consensus networked Euler-Lagrange systems predefined-time control neural adaptive control

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predefined-time adaptive neural dynamic surface tracking control for high-order nonlinear switched systems

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ASIAN JOURNAL OF control 2025年第1期27卷 343-356页

作者： Meng, Zhu Ma, Jiawei Wang, Huanqing Bohai Univ Coll Math Sci Jinzhou 121013 Liaoning Peoples R China Northeastern Univ Coll Informat Sci & Engn Shenyang Peoples R China

In this article, the issue of adaptive predefined-time control for high-order switched systems is researched. Neural networks (NNs) are introduced to approximate the uncertain nonlinear functions. In particular, a novel predefined-time convergence filter is proposed to refrain from the problem of repeated differentiation of virtual controllers. On the basis of the backstepping recursion technique and the common Lyapunov function (CLF) approach, a neural adaptive predefined-time dynamic surface control (DSC) scheme is proposed that can demonstrate all the signals in closed-loop systems are bounded and the tracking error can converge to a small area near zero within predefined time. The simulation results illustrate the effectiveness of the proposed control scheme.

关键词： common Lyapunov function high-order switched systems predefined-time control predefined-time filter

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predefined-time adaptive fuzzy control for nonlinear output constraint systems with unknown backlash-like hysteresis via command filtering

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INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE 2025年第4期56卷 767-785页

作者： Jiang, Yaling Su, Yakun Bohai Univ Sch Math Sci Jinzhou 121000 Peoples R China

In this article, the predefined-time adaptive fuzzy control problem for strict-feedback nonlinear systems with asymmetric time-varying output constraint and unknown backlash-like input hysteresis is considered. An innovative predefined-time adaptive control method, in which utilises unified barrier function (UBF) to deal with the output constraint problem and adopts a differential equation to represent the unknown backlash-like hysteresis, is presented by combining a novel command filter with backstepping technology. Fuzzy logic systems (FLSs) are employed to estimate the unknown nonlinearities. Moreover, by designing appropriate parameters, the constructed control strategy ensures that all signals are predefined-time bound and the tracking error stays in a small neighbourhood adjacent zero. Ultimately, two simulation examples are given to prove the effectiveness of the presented control algorithm.

关键词： Adaptive fuzzy control asymmetric time-varying output constraint unknown Backlash-like hysteresis predefined-time control command filter

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Command-filter based predefined-time neural adaptive decentralized control for interconnected systems with dynamic uncertainties

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COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION 2025年 143卷

作者： Liu, Zhucheng Yang, Feisheng Li, Heng Northwestern Polytech Univ Sch Automat Xian 710129 Shaanxi Peoples R China BYD Automobile Co Ltd Shenzhen 518000 Guangdong Peoples R China

This article studies the predefined-time controller construction problem for non-strict feedback nonlinear large-scale interconnected systems including unmodeled dynamics and dynamic disturbances. The uncertain nonlinearities and interconnections in the studied systems are universally approximated by neural networks. The observable dynamic signals created by the constructed auxiliary systems are utilized to alleviate the impacts of unmodeled state dynamics. Then, a neural adaptive predefined-time decentralized controller is developed via command filtered backstepping technology. The convergence time bound by the proposed control strategy is more flexible than conventional fixed-time control method. Moreover, through adding the compensation signal terms to the entire Lyapunov energy function, all variables in the controlled system are proved to be predefined-time bounded. The simulation shows the validity and superiority of the presented controller.

关键词： Nonlinear interconnected systems Unmodeled dynamics Command filtered backstepping predefined-time control

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