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L. Chen, Y. Xie, Y. Wang, S. Ge, and F.-Y. Wang, “Sustainable mining in the era of artificial intelligence,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 1, pp. 1–4, Jan. 2024. doi: 10.1109/JAS.2023.124182 

M. Fu, “A tutorial on quantized feedback control,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 1, pp. 5–17, Jan. 2024. doi: 10.1109/JAS.2023.123972

> Delves into quantized feedback control, tackling the challenges associated with transmitting feedback information, including measurements and control signals, over digital networks. Additionally, it explores strategies to mitigate the impact of quantization errors.

> Examined topics include minimal information for effective control, quantizer design, strategies for quantized control and estimation, achieving consensus control with quantized data, and high-precision tracking using quantized measurements.

D. Wang, N. Gao, D. Liu, J. Li, and F. Lewis, “Recent progress in reinforcement learning and adaptive dynamic programming for advanced control applications,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 1, pp. 18–36, Jan. 2024. doi: 10.1109/JAS.2023.123843

> Provides a comprehensive survey of recent developments in ADP/RL and its applications in various advanced control fields. Extensive work is summarized for discrete-time and continuous-time systems, respectively.

> The work on the integration of ADP/RL with methods and problems such as event-triggered control, robust stabilization, gaming design, distributed system design and model predictive control is discussed. The ADP architecture is also revisited from a data-driven and RL perspective, demonstrating the broad applicability of ADP.

Z. Pu, Y. Pan, S. Wang, B. Liu, M. Chen, H. Ma, and Y. Cui, “Orientation and decision-making for soccer based on sports analytics and AI: A systematic review,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 1, pp. 37–57, Jan. 2024. doi: 10.1109/JAS.2023.123807 

> Conduct a comprehensive literature review of soccer analysis, evaluation, and decision-making from an interdisciplinary perspective combing professional sports analytics and AI research. 

> An OODA loop concept is adopted to characterize soccer match analysis, evaluation, and decision support process. Specifically, methods and algorithms for orientation and decision making are systematically addressed. 

> Both real-world and virtual soccer matches in data supports, algorithms, and applications are discussed.

Q. Zhao, L. Shu, K. Li, M. Ferrag, X. Liu, and Y. Li, “Security and privacy in solar insecticidal lamps Internet of things: Requirements and challenges,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 1, pp. 58–73, Jan. 2024. doi: 10.1109/JAS.2023.123870 

> Divide the SIL-IoT security requirements into six categories, namely privacy, authentication, confidentiality, access control, availability, and integrity.

> Describe the SIL-IoT privacy and security solutions, as well as the blockchain-based solutions.

> Discuss the challenges and future research directions of SIL-IoT.

B. Qu, Z. Wang, B. Shen, H. Dong, and H. Liu, “Anomaly-resistant decentralized state estimation under minimum error entropy with fiducial points for wide-area power systems,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 1, pp. 74–87, Jan. 2024. doi: 10.1109/JAS.2023.123795 

> A novel decentralized state estimation algorithm is developed for the wide-area power system which is divided into several non-overlapping areas.

> An augmented model is constructed to improve the data redundancy with the aid of unscented transformation approach and statistical linearization approach.

> The minimum error entropy with fiducial points criterion is adopted in the state estimator design to enhance the resistance against measurement with anomalies.

C. Tang, B. Yang, X. Xie, G. R. Chen, M. Al-qaness, and Y. Liu, “An incentive mechanism for federated learning: A continuous zero-determinant strategy approach,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 1, pp. 88–102, Jan. 2024. doi: 10.1109/JAS.2023.123828 

> Model the interaction among participants in the FL as a continuous iterative game, based on which the ZD strategies are extended to the CZD strategies.

> Design an incentive mechanism for FL based on the CZD strategies, but also enhance the efficiency of FL. 

> Combine numerical and real experiments to validate the advantages of the proposed method in simulations.

M. Ye, Q.-L. Han, L. Ding, S. Xu, and G. Jia, “Distributed Nash equilibrium seeking strategies under quantized communication,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 1, pp. 103–112, Jan. 2024. doi: 10.1109/JAS.2022.105857 

> Designing distributed Nash equilibrium seeking strategies under quantized communication.

> Accommodating games under both undirected and directed topologies.

> Analysing the effects of both logarithmic quantizers and uniform quantizers.

Y. Lu, J. Ma, X. Mei, J. Huang, and X.-P. Zhang, “Feature matching via topology-aware graph interaction model,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 1, pp. 113–130, Jan. 2024. doi: 10.1109/JAS.2023.123774 

> A graph interaction model is proposed for feature matching problem.

> Show the proposed model can be solved globally using graph-cut technique.

> A topology-aware relationship is designed to capture the geometric relationship.

Z. Wang, Y. Wang, and Z. Kowalczuk, “Adaptive optimal discrete-time output-feedback using an internal model principle and adaptive dynamic programming,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 1, pp. 131–140, Jan. 2024. doi: 10.1109/JAS.2023.123759 

> Used a linear combination of delayed signals to transform the output regulation problem with external interference into a stabilization regulation problem without external interference.

> Used an output feedback method, which avoids measuring all state information of the system and reduces the use of a large number of sensors while meeting the performance requirements of the controller.

L. D’Alfonso, F. Giannini, G. Franzè, G. Fedele, F. Pupo, and G. Fortino, “Autonomous vehicle platoons in urban road networks: A joint distributed reinforcement learning and model predictive control approach,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 1, pp. 141–156, Jan. 2024. doi: 10.1109/JAS.2023.123705 

> Design of MPC controllers that take advantage of the platoon topology.

> Most of computations performed by the leader for reducing computational complexity.

> Reinforcement learning is the leader job.

R. Wang, Z. Zhou, K. Li, T. Zhang, L. Wang, X. Xu, and X. Liao, “Learning to branch in combinatorial optimization with graph pointer networks,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 1, pp. 157–169, Jan. 2024. doi: 10.1109/JAS.2023.124113 

> Propose using neural networks to automatically learn these branching heuristics.

> In addition the typical graph features that are commonly explored, global and historical features are designed in this work, providing a more comprehensive and richer representation of the problem state.

> Introduce an innovative model that combines the graph neural network with a pointer mechanism.

G.-P. Liu, “Control strategies for digital twin systems,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 1, pp. 170–180, Jan. 2024. doi: 10.1109/JAS.2023.123834

> A novel architecture of digital twin control systems is proposed for practical control applications.

> To make full use of the advantages of digital twins, several digital twin control schemes are presented.

> Proposed digital twin control strategies can effectively deal with practical control challenging issues.

X. Tang, Y. Yang, T. Liu, X. Lin, K. Yang, and S. Li, “Path planning and tracking control for parking via soft actor-critic under non-ideal scenarios,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 1, pp. 181–195, Jan. 2024. doi: 10.1109/JAS.2023.123975 

> Parking deviations of existing vehicles have an impact on automatic parking.

> This impact is evaluated in terms of safety, comfort, deviation, and efficiency.

> Parking is decomposed to several simplify tasks, improve parking performance.

C. Zhu, X. Han, and X. Li, “Analysis and design of time-delay impulsive systems subject to actuator saturation,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 1, pp. 196–204, Jan. 2024. doi: 10.1109/JAS.2023.123720 

> Considered a class of impulsive systems involving delayed impulses and input saturation due to the fact that it is regarded as a better way to model many practical problem, which is is rarely considered in the literature.

> An optimization problem on designing controller is presented in order to maximize the domain of attraction. A relation between impulse action and the estimate of the domain of attraction is established, which was excluded in the existing results.

> Proposed results improve and extend some recent publications.

Z. Zhang, H. Jiang, D. Shen, and S. Saab, “Data-driven learning control algorithms for unachievable tracking problems,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 1, pp. 205–218, Jan. 2024. doi: 10.1109/JAS.2023.123756 

> Characterize the concept of the unachievable tracking problem.

> Demonstrate the necessity of gradient information in achieving the control objective.

> Introduce a design for an input-output-driven learning gain matrix.

D. Luo, Y. Wang, and Y. Song, “Practical prescribed time tracking control with bounded time-varying gain under non-vanishing uncertainties,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 1, pp. 219–230, Jan. 2024. doi: 10.1109/JAS.2023.123738 

> Proposed method, with the aid of a time-varying scaling function that grows monotonically with time and maintains boundedness at and beyond the settling time, does not involve infinite control gain anytime during system operation making PTC practical and linking PTC with its practical version analytically.

> Without using any prior information on the upper or lower bound of system control gain, the proposed control is able to settle the tracking error in the neighborhood of the origin within the prescribed time.

> Developed solution is truly global, allowing the system to operate on the entire time interval, yet is able to deal with non-vanishing and mismatched uncertainties, leading to practical and global prescribed time tracking control solution for a larger class of nonlinear systems.

Y. Liu, B. Tian, Y. Lv, L. Li, and F.-Y. Wang, “Point cloud classification using content-based Transformer via clustering in feature space,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 1, pp. 231–239, Jan. 2024. doi: 10.1109/JAS.2023.123432 

> Design PointConT, a simple yet powerful architecture, can establish long-range feature dependencies and tackle the high-complexity issue of global Transformer for point clouds.

> Propose a content-based attention mechanism, which clusters the sampled points with similar features into the same class and computes the self-attention within each class.

> Design an Inception feature aggregator to combine high-frequency and low-frequency information in a parallel manner.

D. You and S. Wang, “Non-deterministic liveness-enforcing supervisor tolerant to sensor-reading modification attacks,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 1, pp. 240–248, Jan. 2024. doi: 10.1109/JAS.2023.123702 

> Liveness enforcement on cyber-physical systems in the presence of sensor-reading modification attacks.

> By using bounded Petri nets as the reference formalism, an algorithm that synthesizes a liveness-enforcing nondeterministic supervisor tolerant to sensor-reading modification attacks is proposed.

> Compared with a previous method synthesizing a liveness-enforcing deterministic supervisor tolerant to sensor-reading modification attacks, the proposed method has lower computational complexity.

F. Yang, H. Dong, Y. Shen, X. Li, and D. Dai, “Protocol-based non-fragile state estimation for delayed recurrent neural networks subject to replay attacks,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 1, pp. 249–251, Jan. 2024. doi: 10.1109/JAS.2023.123936 

C. Liu, Y. Wang, C. Yang, and W. Gui, “Multimodal data-driven reinforcement learning for operational decision-making in industrial processes,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 1, pp. 252–254, Jan. 2024. doi: 10.1109/JAS.2023.123741 

L. Yan, W. Zheng, and F.-Y. Wang, “Heterogeneous image knowledge driven visual perception,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 1, pp. 255–257, Jan. 2024. doi: 10.1109/JAS.2023.123435

Y. Men, J. Sun, and J. Chen, “Control of 2-D semi-Markov jump systems: A view from mode generation,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 1, pp. 258-260, Jan. 2024. doi: 10.1109/JAS.2023.123654 

C. Qian and L. Ding, “Prescribed-time fully distributed Nash equilibrium seeking strategy in networked games,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 1, pp. 261–263, Jan. 2024. doi: 10.1109/JAS.2023.123933 

Z. Wang, S. Gao, Z. Lei, and M. Omura, “An information-based elite-guided evolutionary algorithm for multi-objective feature selection,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 1, pp. 264–266, Jan. 2024. doi: 10.1109/JAS.2023.123810 

M. Sun, J. Liu, L. Ren, and C. Sun, “Fixed-time consensus-based Nash equilibrium seeking,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 1, pp. 267–269, Jan. 2024. doi: 10.1109/JAS.2023.123900

S. Sun, D. Cai, H.-T. Zhang, and N. Xing, “Reinforcement learning-based MAS interception in antagonistic environments,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 1, pp. 270–272, Jan. 2024. doi: 10.1109/JAS.2023.123798 

W. Li and B. Ning, “Autonomous recommendation of fault detection algorithms for spacecraft,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 1, pp. 273–275, Jan. 2024. doi: 10.1109/JAS.2023.123423

J. Shi and M. Ye, “Distributed optimal formation control for unmanned surface vessels by a regularized game-based approach,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 1, pp. 276–278, Jan. 2024. doi: 10.1109/JAS.2023.123930