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Unified Barrier Function Based Approach for Practical Fixed-Time Control of State-Constrained Nonlinear System

Journal of systems Science & Complexity 2025年第2期38卷 782-804页

作者： GENG Fan DONG Yi HONG Yiguang College of Electronic and Information Engineering National Key Laboratory of Autonomous Intelligent Unmanned Systems Frontiers Science Center for Intelligent Autonomous Systems Ministry of Education Tongji University

This paper considers the practical fixed-time tracking control problem for a state constrained pure-feedback nonlinear system. A new barrier function is first proposed to handle various asymmetric time-varying constraints and unify the cases with and without state constraints. Then a low-cost neural network based adaptive fixed-time controller is constructed by further combining the dynamic surface control, which overcomes the technical problems of overparametrization and singularity in the backstepping procedure. The proposed design guarantees that the tracking error converges to a small neighbourhood of zero in a fixed time while satisfying the state constraints as a priority task without imposing feasibility conditions on the virtual controllers. Simulation results validate the effectiveness of the proposed adaptive fixed-time tracking control strategy.

关键词： Barrier function fixed-time control nonlinear system state constraint

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Constraint-Feature-Guided Evolutionary Algorithms for Multi-Objective Multi-Stage Weapon-Target Assignment Problems

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Journal of systems Science & Complexity 2025年第3期38卷 972-999页

作者： WANG Danjing XIN Bin WANG Yipeng ZHANG Jia DENG Fang WANG Xianpeng School of Automation Beijing Institute of Technology National Key Laboratory of Autonomous Intelligent Unmanned Systems National Frontiers Science Center for Industrial Intelligence and Systems Optimization Northeastern University

The allocation of heterogeneous battlefield resources is crucial in Command and Control(C2). Balancing multiple competing objectives under complex constraints so as to provide decisionmakers with diverse feasible candidate decision schemes remains an urgent challenge. Based on these requirements, a constrained multi-objective multi-stage weapon-target assignment(CMOMWTA) model is established in this paper. To solve this problem, three constraint-feature-guided multi-objective evolutionary algorithms(CFG-MOEAs) are proposed under three typical multi-objective evolutionary frameworks(i.e., NSGA-Ⅱ, NSGA-Ⅲ, and MOEA/D) to obtain various high-quality candidate decision schemes. Firstly, a constraint-feature-guided reproduction strategy incorporating crossover,mutation, and repair is developed to handle complex constraints. It extracts common row and column features from different linear constraints to generate the feasible offspring population. Then, a variable-length integer encoding method is adopted to concisely denote the decision schemes. Moreover,a hybrid initialization method incorporating both heuristic methods and random sampling is designed to better guide the population. Systemic experiments are conducted on three CFG-MOEAs to verify their effectiveness. The superior algorithm CFG-NSGA-Ⅱ among three CFG-MOEAs is compared with two state-of-the-art CMOMWTA algorithms, and extensive experimental results demonstrate the effectiveness and superiority of CFG-NSGA-Ⅱ.

关键词： constrained multi-objective optimization problem constraint handling Evolutionary algorithms weapon-target assignment

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Distributed gradient-free and projection-free algorithm for stochastic constrained optimization

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Autonomous intelligent systems 2024年第1期4卷 320-337页

作者： Jie Hou Xianlin Zeng Chen Chen National Key Laboratory of Autonomous Intelligent Unmanned Systems School of AutomationBeijing Institute of TechnologyBeijing100081China

Distributed stochastic zeroth-order optimization(DSZO),in which the objective function is allocated over multiple agents and the derivative of cost functions is unavailable,arises frequently in large-scale machine learning and reinforcement *** paper introduces a distributed stochastic algorithm for DSZO in a projection-free and gradient-free manner via the Frank-Wolfe framework and the stochastic zeroth-order oracle(SZO).Such a scheme is particularly useful in large-scale constrained optimization problems where calculating gradients or projection operators is impractical,costly,or when the objective function is not differentiable ***,the proposed algorithm,enhanced by recursive momentum and gradient tracking techniques,guarantees convergence with just a single batch per *** significant improvement over existing algorithms substantially lowers the computational *** mild conditions,we prove that the complexity bounds on SZO of the proposed 1 algorithm are O(n/ϵ^(2))andO(n(21/ϵ))for convex and nonconvex cases,*** efficacy of the algorithm is verified on black-box binary classification problems against several competing alternatives.

关键词： Zeroth-order optimization Projection-free method Stochastic constrained optimization Distributed optimization

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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)

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A nonlinear hysteresis compensation control of hydro-viscous drive in air transport operations

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Chinese Journal of Aeronautics 2025年第2期38卷 161-174页

作者： Liang WANG Jianjian LIANG Lin ZHANG Shoukun WANG Junzheng WANG School of Automation and Software Shanxi UniversityTaiyuan 030031China Key Laboratory of Autonomous Intelligent Unmanned Systems School of AutomationBeijing Institute of TechnologyBeijing 100081China

The Hydro-Viscous Drive(HVD)speed regulating system finds extensive application in air transport transmission systems to regulate the stepless speed or conduct overload ***,its intrinsic hysteretic behaviors,such as the asymmetric hysteretic and dead zone,could introduce inaccuracy and delay in control applications,posing challenges to system *** paper investigates a Nonlinear Hysteresis Compensation Control(NHCC)that consists of two parts to control the HVD output speed by operating the valve under different engine operating *** the first part,the Inverse Hysteresis Compensator(IHC)based on major loop data is introduced for the asymmetric hysteresis characterization and compensation of the HVD speed control system of the power generation and distribution,which aims to reduce the hysteresis and dead zone effect and expand the effective input *** the second part,the Active Disturbance Rejection Controller(ADRC)is employed to mitigate the hysteresis effects of the compensated system and remove the steady-state error,which allows real-time compensation of the estimated perturbations as state feedback to achieve the required *** experimental laboratory station has been fabricated to evaluate the proposed *** test results show that the NHCC method can regulate the fan speed to the desired value(45 r/min at steady state)and broaden the effective input range to the full range under different engine ***,the proposed control method can reduce the non-linearity of the input and output curves(from 18%to 4%)and compensate for the asymmetric hysteresis(from 38%to 5%).

关键词： Hydro-viscous drive Nonlinear hysteresis compensation Inverse hysteresis compensation Speed regulating system ADRC

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Gaussian Process Regression Based Pose Tracking Control for Multiple Spacecraft Rendezvous 7th

Gaussian Process Regression Based Pose Tracking Control for...

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7th Chinese Conference on Swarm Intelligence and Cooperative Control, CCSICC 2023

作者： Jiang, Renjian Sun, Liang Key Laboratory of Intelligent Bionic Unmanned Systems of Ministry of Education School of Intelligence Science and Technology University of Science and Technology Beijing Beijing100083 China

ISBN: (纸本)9789819733279

This paper proposes a data-based learning robust adaptive pose tracking controller for multiple spacecraft rendezvous with unknown dynamic uncertainties. Gaussian processes (GP) are used to accurately model and estimate unknown dynamic perturbations. In the case of approximate estimation error and external disturbances, a robust pose tracking controller is proposed. The stability of the closed-loop system is conformed by Lyapunov theory and the results of this paper is proved by a simulation example. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Closed loop systems

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A zeroth-order stochastic implicit method for bilevel-structured actor-critic schemes

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Science China(Information Sciences) 2025年第5期68卷 53-71页

作者： Haochen TAO Shisheng CUI Zhuo LI Jian SUN School of Automation Beijing Institute of Technology National Key Laboratory of Autonomous Intelligent Unmanned Systems School of AutomationBeijing Institute of Technology Beijing Institute of Technology Chongqing Innovation Center

Reinforcement learning algorithms are central to the cognition and decision-making of embodied intelligent agents. A bilevel optimization(BO) modeling approach, along with a host of efficient BO algorithms, has been proven to be an effective means of addressing actor-critic(AC) policy optimization problems. In this work, based on a bilevelstructured AC problem model, an implicit zeroth-order stochastic algorithm is developed. A locally randomized spherical smoothing technique, which can be applied to nonsmooth nonconvex implicit AC formulations and avoid the closed-form lower-level mapping, is introduced. In the proposed zeroth-order scheme, the gradient of the implicit function can be approximated through inexact lower-level value estimations that are practically available. Under suitable assumptions,the algorithmic framework designed for the bilevel AC method is characterized by convergence guarantees under a fixed stepsize and smoothing parameter. Moreover, the proposed algorithm is equipped with the overall iteration complexity of O(n2L20 L20?-1). The convergence performance of the proposed algorithm is verified through numerical simulations.

关键词： actor-critic bilevel optimization zeroth-order algorithm implicit programming stochastic approximation

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Distributed Momentum-Based Frank-Wolfe Algorithm for Stochastic Optimization

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IEEE/CAA Journal of Automatica Sinica 2023年第3期10卷 685-699页

作者： Jie Hou Xianlin Zeng Gang Wang Jian Sun Jie Chen National Key Laboratory of Autonomous Intelligent Unmanned Systems School of AutomationBeijing Institute of TechnologyBeijing 100081China National Key Laboratory of Autonomous Intelligent Unmanned Systems School of AutomationBeijing Institute of TechnologyBeijing 100081 Beijing Institute of Technology Chongqing Innovation Center Chongqing 401120China School of Electronic and Information Engineering Tongji UniversityShanghai 200082and also with the National Key Laboratory of Autonomous Intelligent Unmanned Systemsthe School of AutomationBeijing Institute of TechnologyBeijing 100081China IEEE

This paper considers distributed stochastic optimization,in which a number of agents cooperate to optimize a global objective function through local computations and information exchanges with neighbors over a *** optimization problems are usually tackled by variants of projected stochastic gradient ***,projecting a point onto a feasible set is often *** Frank-Wolfe(FW)method has well-documented merits in handling convex constraints,but existing stochastic FW algorithms are basically developed for centralized *** this context,the present work puts forth a distributed stochastic Frank-Wolfe solver,by judiciously combining Nesterov's momentum and gradient tracking techniques for stochastic convex and nonconvex optimization over *** is shown that the convergence rate of the proposed algorithm is O(k^(-1/2))for convex optimization,and O(1/log_(2)(k))for nonconvex *** efficacy of the algorithm is demonstrated by numerical simulations against a number of competing alternatives.

关键词： Distributed optimization Frank-Wolfe(FW)algorithms momentum-based method stochastic optimization

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Safe motion planning and formation control of quadruped robots

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Autonomous intelligent systems 2024年第1期4卷 38-49页

作者： Zongrui Ji Yi Dong College of Electronic and Information Engineering National Key Laboratory of Autonomous Intelligent Unmanned SystemsFrontiers Science Center for Intelligent Autonomous SystemsMinistry of EducationTongji UniversityShanghai 200092China

This paper introduces a motion planning and cooperative formation control approach for quadruped robots and multi-agent ***,in order to improve the efficiency and safety of quadruped robots navigating in complex environments,this paper proposes a new planning method that combines the dynamic model of quadruped robots and a gradient-optimized obstacle avoidance strategy without Euclidean Signed Distance *** framework is suitable for both static and slow dynamic obstacle environments,aiming to achieve multiple goals of obstacle avoidance,minimizing energy consumption,reducing impact,satisfying dynamic constraints,and ensuring trajectory *** approach differs in that it reduces energy consumption throughout the movement from a new ***,this method effectively reduces the impact of the ground on the robot,thus mitigating the damage to its ***,we combine the dynamic control barrier function and the virtual leader-follower model to achieve efficient and safe formation control through model predictive ***,the proposed algorithm is validated through both simulations and real-world scenarios testing.

关键词： Efficient motion planning Dynamic model Safety-critical Model predictive control

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Control Barrier Navigation Functions for Multi-Agent System Under Signal Temporal Logic Tasks

Control Barrier Navigation Functions for Multi-Agent System ...

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2023 IEEE International Conference on unmanned systems, ICUS 2023

作者： Tian, Chang Yang, Yan Shi, Zhongjiao Liu, Zhijie Ministry of Education Shunde Innovation School University of Science and Technology Key Laboratory of Intelligent Bionic Unmanned Systems Guangdong Beijing China University of Science and Technology Beijing Key Laboratory of Intelligent Bionic Unmanned Systems Ministry of Education Beijing China School of Aerospace Engineering Beijing Institute of Technology Beijing China

ISBN: (纸本)9798350316308

Motivated by the recent work about signal temporal logic and control barrier functions, we try to study the problem of multi-agent planning with control barrier functions under signal temporal logic tasks. Through the use of navigation functions, we possess the ability to precisely describe the workspace. Then we combine these functions with more information such as time limits to build control barrier navigation functions. Finally we design a coupled controller to realize the communication and path planning between multi-agents with high efficiency. In addition, this approach can also handle simple deadlocks. © 2023 IEEE.

关键词： Temporal logic

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