本期导读

主题

迁移学习、模糊信息系统决策、数据驱动控制、分布式网络、时变延迟、反馈控制、多智能体系统、自适应控制、多目标优化、机器人、异常检测...

全球科研机构

美国University of Texas at Arlington、Florida Atlantic University、福特公司；英国University of Birmingham；德国University of Stuttgart；加拿大University of Regina、Laval University、University of Manitoba；新加坡Nanyang Technological University、National University of Singapore、Singapore University of Technology and Design；日本Chiba University、Tokyo University of Technology、Kumamoto University；韩国Pusan National University；浙江大学、同济大学、东北大学、西安电子科技大学、南京理工大学、华中科技大学、山东大学、重庆大学...

 

H. H. Wang and Q.-L. Han, “The distribution of zeros of quasi-polynomials,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 2, pp. 301–304, Feb. 2023. 

doi: 10.1109/JAS.2023.123597 

W. Zhang, L. F. Deng, L. Zhang, and  D. R. Wu,  “A survey on negative transfer,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 2, pp. 305–329, Feb. 2023. 

doi: 10.1109/JAS.2022.106004 

> Performs the first comprehensive review of approaches to overcome or mitigate NT, a long-standing and challenging problem in transfer learning.

> Provides the definition of NT and its reasons, and reviews over fifty representative approaches for overcoming/mitigating NT, according to three categories: domain similarity estimation, safe transfer, and NT mitigation.

> Provides guidelines on NT task constructions and baseline selections, and publicizes an open-source benchmark for NT study with three datasets and over twenty algorithms.

J. M. Zhan, J. J. Wang, W. P. Ding, and  Y. Y. Yao,  “Three-way behavioral decision making with hesitant fuzzy information systems: Survey and challenges,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 2, pp. 330–350, Feb. 2023. 

doi: 10.1109/JAS.2022.106061 

> A brief historical account of the three topics is provided.

> Three-way behavioral decision making with hesitant fuzzy information systems are reviewed.

> Key challenges and future research directions are pointed out.

X. Wang, J. Sun, G. Wang, F. Allgöwer, and  J. Chen,  “Data-driven control of distributed event-triggered network systems,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 2, pp. 351–364, Feb. 2023. 

doi: 10.1109/JAS.2023.123225

> A data-driven event-triggered control of a class of unknown discrete-time interconnected systems using purely input-state data.

> A novel dynamic distributed event-triggered transmission scheme only involving the discrete-time state information of each subsystem and its neighbor(s) at sampling instants.

> Model-based and data-driven methods for co-designing the controller and the event-triggering matrices, based on discrete-time looped-functional approach.

Y. Rahman, A. Sharma, M. Jankovic, M. Santillo, and  M. Hafner,  “Driver intent prediction and collision avoidance with barrier functions,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 2, pp. 365–375, Feb. 2023. 

doi: 10.1109/JAS.2023.123210 

> Driver Intent Prediction.

> Control Barrier Functions.

> Collision Avoidance Systems for Autonomous Vehicles.

M. Ye, D. Li, Q.-L. Han, and  L. Ding,  “Distributed Nash equilibrium seeking for general networked games with bounded disturbances,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 2, pp. 376–387, Feb. 2023. 

doi: 10.1109/JAS.2022.105428

> A reduced-order disturbance observer-based approach to anti-disturbance distributed Nash equilibrium seeking for games is proposed.

> A signum function based distributed algorithm is proposed to attenuate disturbances for games with second-order integrator-type players.

> Theoretic analysis is conducted to ensure the convergence of the proposed methods. 

X. Yang, J. Yan, C. C. Hua, and  X. P. Guan,  “Position measurement based slave torque feedback control for teleoperation systems with time-varying communication delays,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 2, pp. 388–402, Feb. 2023. 

doi: 10.1109/JAS.2022.106076 

> An I&I based velocity observer is developed, and meanwhile the sufficient conditions for exponential convergence are established.

> With the estimated velocity from observer, a slave-torque feedback control algorithm is designed to make the slave manipulator follow the trajectory of master manipulator.

> A delay-dependent convergence criterion is proposed based on the constructed Lyapunov-Krasovskii functional.

C. H. Zhang, L. Chang, L. T. Xing, and  X. F. Zhang,  “Fixed-time stabilization of a class of strict-feedback nonlinear systems via dynamic gain feedback control,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 2, pp. 403–410, Feb. 2023. 

doi: 10.1109/JAS.2023.123408 

> Presents a novel fixed-time stabilization control method for a class of strict-feedback nonlinear systems involving unmodelled system dynamics.

> Two dynamic parameters are delicately designed by utilizing the Lyapunov method, ensuring that all the closed-loop system states are globally fixed-time stable. 

> Two designed dynamic parameters are dependent on system states rather than a time-varying function, thus the proposed controller is still valid beyond the given fixed-time convergence instant.

J. Y. Ma, K. N. Zhang, and  J. J. Jiang,  “Loop closure detection via locality preserving matching with global consensus,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 2, pp. 411–426, Feb. 2023. 

doi: 10.1109/JAS.2022.105926 

> Design an incremental strategy to make the soundness FIRe applied in LCD.

> Propose LPM-GC to realize feature matching within a few milliseconds in LCD.

> A robust, computationally and memory-wise efficient LCD system is designed.

P. Yu, K.-Z. Liu, X. D. Liu, X. L. Li, M. Wu, and  J. She,  “Robust consensus tracking control of uncertain multi-agent systems with local disturbance rejection,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 2, pp. 427–438, Feb. 2023. 

doi: 10.1109/JAS.2023.123231 

> By only using the output information of the agents and its neighbors, a new consensus tracking protocol with 2-DOF of active disturbance-rejection control is devised.

> Condition for local disturbance rejection is derived, which clarifies the superiority over global disturbance rejection.

> Regardless of the disturbance input channels, asymptotic performance is theoretically guaranteed when an internal model of disturbances is incorporated.

Y. Y. Zhao, F. Y. Xiao, M. Aritsugi, and  W. P. Ding,  “A quantum Tanimoto coefficient fidelity for entanglement measurement,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 2, pp. 439–450, Feb. 2023. 

doi: 10.1109/JAS.2022.106079 

> A novel QTC fidelity that considers both overlap and separation between quantum states is proposed.

> Three discrimination coefficients are proposed for quantum states based on QTC fidelity.

> QTC fidelity-based discrimination coefficients are applied to measure entanglement.

K. Zhao, C. Y. Wen, Y. D. Song, and  F. L. Lewis,  “Adaptive uniform performance control of strict-feedback nonlinear systems with time-varying control gain,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 2, pp. 451–461, Feb. 2023. 

doi: 10.1109/JAS.2022.106064 

> By constructing a unified function and a unique scaling function, the proposed control is flexible to handle the global or symmetric semi-global performance cases uniformly just by selecting the initial value of the time-varying scaling function properly, making the controller re-design and stability re-analysis not required.

> By defining an ENF and imposing a condition on the update law of Nussbaum argument, the developed control relaxes the complicated calculation and proof in the existing results.

> By extracting the core function information from the non- parametric uncertainty, no approximator is required, despite unknown control directions.

B. Y. Li, Q. M. Yang, and  I. Kamwa,  “A novel Stackelberg-game-based energy storage sharing scheme under demand charge,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 2, pp. 462–473, Feb. 2023. 

doi: 10.1109/JAS.2023.123216

> A novel Stackelberg-game-based ESS sharing scheme is proposed.

> All the participants are assumed to be selfish and not collaborating, as in the practical scenarios.

> Demand charge and TOU price are considered.

M. S. Song, F. Zhang, B. X. Huang, and  P. F. Huang,  “Anti-disturbance control for tethered aircraft system with deferred output constraints,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 2, pp. 474–485, Feb. 2023. 

doi: 10.1109/JAS.2023.123222 

> Unlike the previous works, the paper considers the fact that the main aircraft flies unsteadily.

> Unlike the current ESO, the modified shifting function-based ESO avoids the peaking phenomenon.

> Improved output constrained controller solves the deferred output constraint problem.

X. Y. Zheng, B. T. Han, and  Z. Ni,  “Tourism route recommendation based on a multi-objective evolutionary algorithm using two-stage decomposition and Pareto layering,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 2, pp. 486–500, Feb. 2023. 

doi: 10.1109/JAS.2023.123219 

> Crowding degree mechanism can determine the boundary region and the intermediate solution in multi-objective evolutionary algorithm.

> A strategy for dividing sub regions Pareto layering structure, dnd using the penalty-based boundary intersection values in the sub-regions can improve the diversity of solutions.

> Combining the two-stage approach with pareto layering, the distribution and diversity of the solutions for multi-objective evolutionary algorithm.

Y. Yang, J. T. Han, Z. J. Liu, Z. J. Zhao, and  K.-S. Hong,  “Modeling and adaptive neural network control for a soft robotic arm with prescribed motion constraints,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 2, pp. 501–511, Feb. 2023. 

doi: 10.1109/JAS.2023.123213 

> Soft robotic arm is modeled using screw theory to prevent chirality caused by local axis systems.

> A NN-based adaptive feedback controller is designed to handle uncertainty.

> Motion limits and performance functions of the soft robotic arm are turned into error bounds.

J. Chen, K. Y. Luo, C. B. Tang, Z. Zhang, and  X. Li,  “Optimizing polynomial-time solutions to a network weighted vertex cover game,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 2, pp. 512–523, Feb. 2023. 

doi: 10.1109/JAS.2022.105521 

> Establish a novel general game model for the WVC problem, and define three cover states to describe the WVC problem.

> Reveal the relationship between the cover states and the SNEs of the established game model.

> Propose a GAA with memory length m=1, which can guarantee to obtain an SNE in polynomial time.

W. T. Mao, G. S. Wang, L. L. Kou, and  X. H. Liang,  “Deep domain-adversarial anomaly detection with one-class transfer learning,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 2, pp. 524–546, Feb. 2023. 

doi: 10.1109/JAS.2023.123228 

> Propose a new deep transfer learning algorithm for one-class anomaly detection.

> Build a hypersphere adversarial training mechanism to transfer detection rule.

> Theoretically analyze model reliability to avoid invalid and negative transfer.

J. Li, Q. Zhou, X. He, and H. M. Xu, “Driver-centric velocity prediction with multidimensional fuzzy granulation,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 2, pp. 547–549, Feb. 2023. 

doi: 10.1109/JAS.2022.105998 

Z. Y. Zhang, Y. Qin, J. P. Wang, H. Li, and R. L. Deng, “Detecting the one-shot dummy attack on the power industrial control processes with an unsupervised data-driven approach,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 2, pp. 550–553, Feb. 2023. 

doi: 10.1109/JAS.2023.123243 

B. W. Zhou, C. Xi, D. S. Yang, Q. Y. Sun, and H. G. Zhang, “A distributed self-consistent control method for electric vehicles to coordinate low-carbon transportation and energy,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 2, pp. 554–556, Feb. 2023. 

doi: 10.1109/JAS.2023.123240 

Z. Y. Zhang and D. K. Y. Yau, “CoRE: Constrained robustness evaluation of machine learning-based stability assessment for power systems,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 2, pp. 557–559, Feb. 2023. 

doi: 10.1109/JAS.2023.123252 

W. H. Li, K. Y. Qin, M. J. Shi, J. L. Shao, and B. X. Lin, “Dynamic target enclosing control scheme for multi-agent systems via a signed graph-based approach,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 2, pp. 560–562, Feb. 2023. 

doi: 10.1109/JAS.2023.123234 

J. X. Zhang, W. Liu, and Y. M. Li, “Optimal formation control for second-order multi-agent systems with obstacle avoidance,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 2, pp. 563–565, Feb. 2023. 

doi: 10.1109/JAS.2023.123249 

H. Y. Cheng, B. Fang, Q. Liu, J. H. Zhang, and J. Hong, “Visual feedback disturbance rejection control for an amphibious bionic stingray under actuator saturation,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 2, pp. 566–568, Feb. 2023. 

doi: 10.1109/JAS.2023.123237 

Y. Lei, Y.-W. Wang, X.-K. Liu, and W. Yang, “Prescribed-time stabilization of singularly perturbed systems,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 2, pp. 569–571, Feb. 2023. 

doi: 10.1109/JAS.2023.123246 

Z. Q. Han, Y. T. Wang, and Q. Sun, “Straight-path following and formation control of USVs using distributed deep reinforcement learning and adaptive neural network,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 2, pp. 572–574, Feb. 2023. 

doi: 10.1109/JAS.2023.123255