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【当期目录】IEEE/CAA JAS 第7卷 第5期

已有 1365 次阅读 2020-8-28 16:01 |系统分类:博客资讯

导读


最新一期包括大型网络信息物理系统的弹性控制专题,以及关于多智能体系统、智能车辆、深度学习、优化等热点的论文。

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<大型网络信息物理系统的弹性控制>专题


Giuseppe Franzè, Giancarlo Fortino, Xianghui Cao, Giuseppe Maria Luigi Sarnè and Zhen Song, "Resilient Control in Large-Scale Networked Cyber-Physical Systems:Guest Editorial," IEEE/CAA J. Autom. Sinica, vol. 7, no. 5, pp. 1201-1203, Sept. 2020.



Giuseppe Franzè, Domenico Famularo, Walter Lucia and Francesco Tedesco, "A Resilient Control Strategy for Cyber-Physical Systems Subject to Denial of Service Attacks: A Leader-Follower Set-Theoretic Approach," IEEE/CAA J. Autom. Sinica, vol. 7, no. 5, pp. 1204-1214, Sept. 2020.


<Highlights>

  • A predictive control for networked MASs subject to cyber attacks is developed.

  • A dynamical Leader-Follower paradigm is used to face adversities affecting the leader.

  • The LF paradigm avoids iterative information exchange and attack detection procedures.

  • The needed computational resources (CPUs speed, memory, and bandwidth) are modest.




Ning Wang and Xiaojian Li, "Secure Synchronization Control for a Class ofCyber-Physical Systems WithUnknown Dynamics," IEEE/CAA J. Autom. Sinica, vol. 7, no. 5, pp. 1215-1224, Sept. 2020. 


<Highlights>

  • An optimal control law consisting of a feedback control and a compensated feedforward control is proposed to achieve the synchronization, and the feedback control gain matrix is learned by iteratively solving an Algebraic Riccati Equation.

  • A matrix polynomial replacement method is given and it is proved that, the proposed optimal control law can still guarantee the convergence of synchronization errors.



Ya Zhang, Lishuang Du and Frank L. Lewis, "Stochastic DoS Attack Allocation Against Collaborative Estimation in Sensor Networks," IEEE/CAA J. Autom. Sinica, vol. 7, no. 5, pp. 1225-1234, Sept. 2020.


<Highlights>

  • Stochastic DoS attack allocation in networks with multiple sensors is studied.

  • The minimum number of channels needed to attack and how to select them are given.

  • The attack probabilities and power with minimum energy consumption are proposed.


Amir Amini, Amir Asif and Arash Mohammadi, "Formation-Containment Control Using Dynamic Event-Triggering Mechanism for Multi-Agent Systems," IEEE/CAA J. Autom. Sinica, vol. 7, no. 5, pp. 1235-1248, Sept. 2020.


<Highlights>

  • The proposed algorithm includes two novel stages of co-design optimization to simultaneously compute the two sets of parameters.

  • The design optimizations are convex and use the weighted sum approach to enable a structured trade-off between the formation-containment convergence rate and associated communications.



Abenezer Girma, Niloofar Bahadori, Mrinmoy Sarkar, Tadewos G. Tadewos, Mohammad R. Behnia, M. Nabil Mahmoud, Ali Karimoddini and Abdollah Homaifar, "IoT-Enabled Autonomous System Collaboration for Disaster-Area Management," IEEE/CAA J. Autom. Sinica, vol. 7, no. 5, pp. 1249-1262, Sept. 2020.


<Highlights>

  • A framework designed to create a collaborative effort between heterogeneous Unmanned Vehicles and first-responders to make search and rescue operations safer and faster.

  • An effective UAV resource allocation mechanism is implemented using a clustering algorithm technique.

  • A control mechanism for landing UAV on moving UGV platform is implemented for recharging UAVs.

  • To the best of our knowledge, this is the first work that uses AADL for timing analysis in an IoT-enabled autonomous system.



Giancarlo Fortino, Fabrizio Messina, Domenico Rosaci and Giuseppe M. L. Sarnè, "ResIoT: An IoT Social Framework Resilient to Malicious Activities," IEEE/CAA J. Autom. Sinica, vol. 7, no. 5, pp. 1263-1278, Sept. 2020.


<Highlights>

  • A framework for agents operating in an IOT environment, called ResIOT, is proposed.

  • The framework is capable to drive the formation of communities to avoid misleading agents behaviors.

  • The experimental campaign prove that agents have not convenience to performs misleading behaviors in communities.

  • The presented approach is able to detect the malicious agents in the system, with good accuracy.



Alejandro White, Ali Karimoddini and Mohammad Karimadini, "Resilient Fault Diagnosis Under Imperfect Observations–A Need for Industry 4.0 Era," IEEE/CAA J. Autom. Sinica, vol. 7, no. 5, pp. 1279-1288, Sept. 2020. 


<Highlights>

  • A diagnosis tool which can robustly detect, locate, and isolate faults.

  • In case of missed observation, the diagnoser automatically resets and asynchronously resumes the diagnosis process.

  • New concepts of asynchronous detectability and asynchronous diagnosability are introduced.

  • It is formally proved that the proposed diagnoser is capable of diagnosing faults under imperfect observations.



综述

Wenshuo Wang, Xiaoxiang Na, Dongpu Cao, Jianwei Gong, Junqiang Xi, Yang Xing and Fei-Yue Wang, "Decision-Making in Driver-Automation Shared Control: A Review and Perspectives," IEEE/CAA J. Autom. Sinica, vol. 7, no. 5, pp. 1289-1307, Sept. 2020.


<Highlights>

  • Providing a review of decision-making in driver-automation shared control.

  • Discussing human driver models from different perspectives.

  • Providing future challenges and opportunities in driver-automation shared control systems.


Abhinoy Kumar Singh, "Major Development Under Gaussian Filtering Since Unscented Kalman Filter," IEEE/CAA J. Autom. Sinica, vol. 7, no. 5, pp. 1308-1325, Sept. 2020.


<Highlights>

  • This paper reviews the developments in Gaussian filtering since the unscented Kalman filter.

  • The revision is mainly focused on deterministic sigma point based Gaussian filtering.

  • The revision also includes some extensions of Gaussian filtering.

  • Discussed extensions: square-root, Gaussian-sum and continuous-discrete filtering methods.


论文

Wangli He, Zekun Mo, Qing-Long Han and Feng Qian, "Secure Impulsive Synchronization in Lipschitz-Type Multi-Agent Systems Subject to Deception Attacks," IEEE/CAA J. Autom. Sinica, vol. 7, no. 5, pp. 1326-1334, Sept. 2020. 


<Highlights>

  • A mathematical model of leader-following MASs with distributed impulsive control suffered from replacement deception attacks is built. 

  • Sufficient conditions for mean-square bounded synchronization are derived in which the nonzero upper bound of the error is given. 

  • For symmetric networks, how to choose the coupling strength, the impulsive interval and the attack intensity and probability the systems can render are also given.

  • An asymmetric barrier Lyapunov functions based neural control is proposed.

  • All states are guaranteed to stay in the pre-given time-varying ranges within finite time.

  • The system output is driven to track the desired signal as quickly as possible.


Lei Liu, Tingting Gao, Yan-Jun Liu and Shaocheng Tong, "Time-Varying Asymmetrical BLFs Based Adaptive Finite-Time Neural Control of Nonlinear Systems With Full State Constraints," IEEE/CAA J. Autom. Sinica, vol. 7, no. 5, pp. 1335-1343, Sept. 2020.


<Highlights>

  • This paper proposes an adaptive finite-time control approach for a class of strict-feedback systems with asymmetric time-varying full state constraints.

  • Combining with backstepping technique to the constructed controller, the RBFNNs are used to deal with unknown items. In the meantime, the ABLFs are employed to ensure that the state constraints are satisfied.

  • Through the Lyapunov theorem, it is proved that if all the closed-loop signals are bounded and the time-varying asymmetrical constraints are not violated, the tracking error is close to the origin in finite-time.



Arnab Rakshit, Amit Konar and Atulya K. Nagar, "A Hybrid Brain-Computer Interface for Closed-Loop Position Control of a Robot Arm," IEEE/CAA J. Autom. Sinica, vol. 7, no. 5, pp. 1344-1360, Sept. 2020.


<Highlights>

  • A novel scheme of Brain-comanded position-control of a robot arm in a 3-dimensional environment is proposed.

  • Positional overshoot and steady-state error are reduced by an exponential decrease in speed and reversal of turning of the motors as the target position is crossed.

  • The fundamental contribution includes a non-traditional approach to computing transfer function of the position controllerand its parameter setting to attain stability by Root Locus analysis. 



Xuesong Li, Yating Liu, Kunfeng Wang and Fei-Yue Wang, "A Recurrent Attention and Interaction Model for Pedestrian Trajectory Prediction," IEEE/CAA J. Autom. Sinica, vol. 7, no. 5, pp. 1361-1370, Sept. 2020.


<Highlights>

  • Spatio-temporal feature is mined to model the attention, interaction and randomness of motion.

  • Attention module assigns different weights to the input sequence of target in time domain.

  • Spatial pooling module models the social behaviors of neighbors at current and historical moments.



Jamal Banzi, Isack Bulugu and Zhongfu Ye, "Learning a Deep Predictive Coding Network for a Semi-Supervised 3D-Hand Pose Estimation," IEEE/CAA J. Autom. Sinica, vol. 7, no. 5, pp. 1371-1379, Sept. 2020.


<Highlights>

  • A new way of modelling a hand topology using (LDTM) which transforms internal joint locations to an explicit hand representation. This hand representation is more compact and invariant in scale and view angles.

  • Strong hand detector integrated with the deep learning based pose estimator into one pipeline. Therefore, our hand pose estimation is based on the prior knowledge of the human hand.



Haitao Yuan, MengChu Zhou, Qing Liu and Abdullah Abusorrah, "Fine-Grained Resource Provisioning and Task Scheduling for Heterogeneous Applications in Distributed Green Clouds," IEEE/CAA J. Autom. Sinica, vol. 7, no. 5, pp. 1380-1393, Sept. 2020.


<Highlights>

  • An energy cost problem is minimized while strictly meeting latency limits of tasks.

  • Simulated-annealing-based bees algorithm is used to find a real-time solution.

  • SBA properly consumes energy by optimally allocating tasks of heterogeneous in GCs.

  • SBA achieves lower energy cost than its several benchmark scheduling peers can do.



Yiming Cheng, Xu Zhang, Tianhe Liu and Changhong Wang, "Finite-time Control of Discrete-time Systems With Variable Quantization Density in Networked Channels," IEEE/CAA J. Autom. Sinica, vol. 7, no. 5, pp. 1394-1402, Sept. 2020. 


<Highlights>

  • The interested quantization density of networked system is modeled as a class of switched systems with persistent dwell time switching signals.

  • A class of Lyapunov-like functions that are both mode-dependent and quantization density-dependent is developed.

  • The switched system with PDT switching is finite-time bounded and has a prescribed H∞ performance.


Yantao Tian, Yanbo Zhao, Yiran Shi, Xuanhao Cao and Ding-Li Yu, "The Indirect Shared Steering Control Under Double Loop Structure of Driver and Automation," IEEE/CAA J. Autom. Sinica, vol. 7, no. 5, pp. 1403-1416, Sept. 2020.


<Highlights>

  • The indirect shared control under double loop framework is proposed, which divides driver and controller into two independent closed loops so as to obtain the weighted steering angle through authority allocation system.

  • The steering angle arbitration system based on fuzzy inference rules is proposed, which can reduce the impact of faulty operations of driver or controller on driving safety.

  • The active disturbance rejection controller ADRC is used to restrain disturbances and improve the tracking precision of steering angle.


Jing Cheng and Li Chen, "The Fuzzy Neural Network Control Scheme With H∞ Tracking Characteristic of Space Robot System With Dual-arm After Capturing a Spin Spacecraft," IEEE/CAA J. Autom. Sinica, vol. 7, no. 5, pp. 1417-1424, Sept. 2020. 


<Highlights>

  • The pre-impact dynamic equations of open chain dual-arm space robot are established by Lagrangian approach, and the dynamic equations of a spacecraft are obtained by Newton-Euler method.

  • The recurrent fuzzy neural network control scheme is designed for calm motion of unstable closed chain system with uncertain system parameter.


Qiu-Yan He, Yi-Fei Pu, Bo Yu and Xiao Yuan, "Arbitrary-Order Fractance Approximation Circuits With High Order-Stability Characteristic and Wider Approximation Frequency Bandwidth," IEEE/CAA J. Autom. Sinica, vol. 7, no. 5, pp. 1425-1436, Sept. 2020.


<Highlights>

  • This paper discusses an improved rational approximation algorithm of arbitrary-order fractances, which has high order-stability characteristic and wider approximation frequency bandwidth.

  • Compared with the related algorithms, the predistortion exponent of this algorithm is not limited to be zero and has a value between -1 and 1. 

  • Approximation performance comparisons have been made between the corresponding circuit and other types of fractance approximation circuits.

  • A fractance approximation circuit with the impedance function of -2/3-order is designed to verify the practicality of the algorithm.



Long Chen, Linqing Wang, Zhongyang Han, Jun Zhao and Wei Wang, "Variational Inference Based Kernel Dynamic Bayesian Networks for Construction of Prediction Intervals for Industrial Time Series With Incomplete Input," IEEE/CAA J. Autom. Sinica, vol. 7, no. 5, pp. 1437-1445, Sept. 2020.


<Highlights>

  • This study proposes a variational inference method for the KDBN for time series prediction with missing points.

  • There are two inference stages, including the inference of missing inputs and the prediction stage.

  • The proposed method exhibits faster computing time with good performance in experiments.



Yinghua Yang, Xiang Shi, Xiaozhi Liu and Hongru Li, "A Novel MDFA-MKECA Method With Application to Industrial Batch Process Monitoring," IEEE/CAA J. Autom. Sinica, vol. 7, no. 5, pp. 1446-1454, Sept. 2020.


<Highlights>

  • A novel batch process monitoring method MDFA-MKECA is proposed for on-line process monitoring of industry process.  

  • The proposed data feature extraction method can not only effectively extract the feature information of process data with complex characteristics in industrial processes, but also make up for the shortcoming of traditional multivariate statistical process monitoring that cannot handle batch data whose batch length are unequal.

  • For the reheating furnace process, we provide a more refined monitoring method based on MKECA in process monitoring.



Xia Chen, Zhan-Li Sun, Kin-Man Lam and Zhigang Zeng, "A Local Deviation Constraint Based Non-Rigid Structure From Motion Approach," IEEE/CAA J. Autom. Sinica, vol. 7, no. 5, pp. 1455-1464, Sept. 2020. 


<Highlights>

  • An effective model is constructed by considering both the overall estimation error and the variance of reconstruction errors for each frame.

  • An Augmented Lagrange Multipliers (ALM) iterative algorithm is developed to optimize the local deviation-constrained-based estimation model.

  • A convergence analysis is carried out in detail for the model optimization.




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