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Global Consensus of Positive Edge System With Sector Input Nonlinearities

IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 2021年第7期51卷 4057-4066页

作者： Wu, Han Lam, James Su, Housheng Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Image Proc & Intelligent Control Key Lab Educ Minist China Wuhan 430074 Peoples R China Wuhan Univ Sci & Technol Engn Res Ctr Met Automat & Measurement Technol Sch Informat Sci & Engn Wuhan 430081 Peoples R China Univ Hong Kong Dept Mech Engn Hong Kong Peoples R China

This paper investigates the positive edge consensus problems for undirected networks, where each edge is modeled by a continuous-time positive system with sector input nonlinearities. Based on a given nodal network, the corresponding edge network is presented, and some relationships between the given nodal network and its edge network are given. The observer-based protocol for non-negative consensus is proposed. Rigorous theoretical analysis which considers both the input nonlinearities and the positivity constraint is introduced to achieve a global consensus result. Simultaneous stabilization problems are constructed for edge-based non-negative consensus using the maximum and the minimum nonzero eigenvalues of the edge Laplacian matrix. Furthermore, the robustness of the positive edge consensus to parameter perturbation is illustrated. Sufficient non-negative consensus conditions related to the bounds of system matrices are given, and the non-negative edge consensus conditions for star nodal networks are also given only using the vertex number. Iterative linear matrix inequalities (LMIs)/LMI algorithm is presented to obtain the feedback matrix and the observer matrix. The given theoretical results are finally illustrated by some simulations.

关键词： Vehicle dynamics Linear matrix inequalities Observers Topology Complex networks Protocols control systems Edge network observer-based consensus positive system sector nonlinearity

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Machine learning based soft sensor and long-term calibration scheme: A solid oxide fuel cell system case

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INTERNATIONAL JOURNAL OF HYDROGEN ENERGY 2021年第33期46卷 17322-17342页

作者： Zhao, Weiqi Jiang, Jianhua Qin, Hongchuan Li, Xi Li, Jian Huazhong Univ Sci & Technol Educ Minist Image Proc & Intelligent Control Key Lab Sch Artificial Intelligence & Automat Wuhan 430074 Hubei Peoples R China Huazhong Univ Sci & Technol China EU Inst Clean & Renewable Energy Wuhan 430074 Hubei Peoples R China Huazhong Univ Sci & Technol Sch Mat Sci & Engn Wuhan 430074 Hubei Peoples R China

To quickly and accurately obtain the multi-dimensional state in a sealing reactor is critical for the safety and high performance of industrial system. In this work, a generic machine learning based multi-dimensional soft sensor and a long-term calibration scheme is proposed by using the case of steam reforming solid oxide fuel cell (SR-SOFC) system. Firstly, based on a validated SR-SOFC system model, the temporal-spatial temperature distribution (TSTD) characteristics are analyzed and a TSTD characteristic model is constructed by Multivariable Linear Regression. Then, the central node temperature of the stack is estimated by applying the Least Square Support Vector Machine and the SR-SOFC stack temperature distribution is accurately obtained by explaining the TSTD characteristics model with the central node temperature. In addition, the temperature distribution is calibrated by Stochastic Gradient Descent algorithm to eliminate the estimation error resulting from stack degradation in a long term. The simulation results show that the proposed method can obtain the SR-SOFC stack temperature distribution in time and effectively, the average error is less than 1 K. The proposed estimation strategy can be easily expanded to other scenarios with similar operation conditions. (c) 2021 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.

关键词： Soft sensor Solid oxide fuel cell system Temperature distribution Pattern recognition Temporal-spatial characteristics Stack degradation

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Output Multiformation Tracking of Networked Heterogeneous Robotic Systems via Finite-Time Hierarchical control

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IEEE TRANSACTIONS ON CYBERNETICS 2021年第6期51卷 2893-2904页

作者： Liang, Chang-Duo Ge, Ming-Feng Liu, Zhi-Wei Wang, Yan-Wu Karimi, Hamid Reza China Univ Geosci Sch Mech Engn & Elect Informat Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Key Lab Image Proc & Intelligent Control Minist Educ Wuhan 430074 Peoples R China Politecn Milan Dept Mech Engn I-20156 Milan Italy

This article investigates the finite-time output multiformation tracking (OMFT) problem of networked heterogeneous robotic systems (NHRSs), where each robot model involves external disturbances, parametric uncertainties, and possible kinematic redundancy. Besides, the interactions among robotic systems are described as a directed graph with an acyclic partition. Then, several novel practical finite-time hierarchical control (FTHC) algorithms are designed. The convergence analysis of the closed-loop dynamics is extremely difficult due to the lack of effective analysis methods. Based on the mathematics induction and reductio ad absurdum, a new nonsmooth Lyapunov function is proposed to derive the sufficient conditions and settling time functions. Finally, numerical simulations are performed on the NHRS to verify the main results.

关键词： Robot kinematics Convergence Directed graphs Multi-agent systems Task analysis Kinematics Finite-time hierarchical control (FTHC) networked heterogeneous robotic systems (NHRSs) nonsmooth Lyapunov function output multiformation tracking (OMFT)

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Understanding the Robustness of 3D Object Detection with Bird'View Representations in Autonomous Driving

Understanding the Robustness of 3D Object Detection with Bir...

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Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Zijian Zhu Yichi Zhang Hai Chen Yinpeng Dong Shu Zhao Wenbo Ding Jiachen Zhong Shibao Zheng Institute of Image Communication and Network Engineering Shanghai Jiao Tong University Dept. of Comp. Sci. and Tech. THBI Lab Institute for AI Tsinghua University BNRist Center Zhongguancun Laboratory Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Information Materials and Intelligent Sensing Laboratory of Anhui Province School of Computer Science and Technology Anhui University SAIC Motor AI Lab

3D object detection is an essential perception task in autonomous driving to understand the environments. The Bird's-Eye-View (BEV) representations have significantly improved the performance of 3D detectors with camera inputs on popular benchmarks. However, there still lacks a systematic understanding of the robustness of these vision-dependent BEV models, which is closely related to the safety of autonomous driving systems. In this paper, we evaluate the natural and adversarial robustness of various representative models under extensive settings, to fully understand their behaviors influenced by explicit BEV features compared with those without BEV. In addition to the classic settings, we propose a 3D consistent patch attack by applying adversarial patches in the 3D space to guarantee the spatiotemporal consistency, which is more realistic for the scenario of autonomous driving. With substantial experiments, we draw several findings: 1) BEV models tend to be more stable than previous methods under different natural conditions and common corruptions due to the expressive spatial representations; 2) BEV models are more vulnerable to adversarial noises, mainly caused by the redundant BEV features; 3) Camera-LiDARfusion models have superior performance under different settings with multi-modal inputs, but BEV fusion model is still vulnerable to adversarial noises of both point cloud and image. These findings alert the safety issue in the applications of BEV detectors and could facilitate the development of more robust models.

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Head-free, Human Gaze-driven Assistive Robotic System for Reaching and Grasping 40

Head-free, Human Gaze-driven Assistive Robotic System for Re...

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40th Chinese control Conference (CCC)

作者： Yang, Bo Huang, Jian Sun, Menglin Huo, Jun Li, Xiaolong Xiong, Caihua Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Sch Mech Sci & Engn Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol State Key Lab Digital Mfg Equipment & Technol Wuhan 430074 Peoples R China

ISBN: (纸本)9789881563804

Patients with limb dysfunction have limited mobility, which prevents them from performing daily activities. We have developed an assistive robot system with an intuitive head free gaze interface. The system consists of multiple modules, including 3D gaze estimation, head free coordinate transformation, intention recognition, and robot trajectory planning. The robotic assistive system obtains clues from the user's gaze to decode their intentions and implement actions. This allows the user only needs to look at the objects to make the robot system reach, grasp, and bring them to the user. The 3D gaze estimation is evaluated with 5 subjects, showing an overall accuracy of 5.53 +/- 1.2 cm. The integrated system's experimental results show that the success rate is 96% in the implementation of automatic trajectory planning, and the success rate is 92% in the implementation of fixation-based trajectory planning. Finally, the results and work required to improve the system are discussed.

关键词： 3D gaze estimation Intention estimation Gaze-based control Assistive robot

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control languages accepted by labeled spiking neural P systems with rules on synapses

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THEORETICAL COMPUTER SCIENCE 2021年 893卷 60-71页

作者： Zhang, Luping Xu, Fei Ramanujan, Ajeesh Subramanian, K. G. Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Educ Minist China Key Lab Image Informat Proc & Intelligent Control Wuhan 430074 Peoples R China Coll Engn Trivandrum Dept Comp Sci & Engn Thiruvananthapuram 695016 Kerala India Liverpool Hope Univ Sch Math Comp Sci & Engn Hope Pk Liverpool L16 9JD Merseyside England

Spiking neural P systems with rules on synapses (RSSNP systems) are a class of computation models which are inspired by the information processing and communication manner of neurons. In this work, we consider labeled RSSNP systems (lRSSNP systems), where each rule is assigned either with a label chosen from an alphabet Sigma or with the empty label lambda. A string over an alphabet is accepted by an lRSSNP system if the string is processed from left to right by the system in the sense that in a step only rules labeled with the processed symbol or with lambda are used (not both), and the system reaches a final configuration in the moment when the whole string is processed. The set of all accepted strings is categorized as the restricted (computations are done with the application of the rules labeled with symbols from the given alphabet) control language and the unrestricted (rules labeled with lambda are allowed in the computations) control language of the system. We study the language accepting power of lRSSNP systems using only standard spiking rules by comparing the family of control languages of lRSSNP systems with the families of languages in the Chomsky hierarchy. It is proved that restricted lRSSNP systems can accept no more than context-sensitive languages, and unrestricted lRSSNP systems can accept recursively enumerable languages. (c) 2021 Elsevier B.V. All rights reserved.

关键词： Membrane computing Spiking neural P system Rule on synapse controlled mechanism Language

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A memristive dual-slope A/D converter

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INTERNATIONAL JOURNAL OF CIRCUIT THEORY AND APPLICATIONS 2020年第1期48卷 42-55页

作者： Yang, Le Zeng, Zhigang Ma, Zhansong Shan, Wenqi Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Hubei Peoples R China Huazhong Univ Sci & Technol Key Lab Image Proc & Intelligent Control Educ Minist China Wuhan Hubei Peoples R China

As an emerging device, memristor has several excellent properties like changeable memristance, nonvolatility, and nanoscale. Based on complementary metal-oxide-semiconductor (CMOS) dual-slope analog-to-digital (A/D) converter, this paper proposes a memristive dual-slope A/D converter. Owing to the usage of memristor, the proposed memristive A/D converter not only has more compact circuit structure and simpler control timing than the CMOS one but also has advantages over the existing memristive conversion circuits in circuit design and application. For the memristive A/D converter, a conversion process consists of two count procedures. By means of controlling the memristance change in the two count procedures, the A/D converter converts an analog signal to the corresponding digital count value. Meanwhile, the conversion result is inferred according to the circuit structure of the A/D converter. Then, combining the conversion process and PSPICE simulation, this paper analyzes the anti-interference performance of the A/D converter. Further, the robustness of the A/D converter is presented, applying the similar analysis methods. The analysis results demonstrate that the proposed A/D converter has good anti-interference and robustness performances.

关键词： anti-interference dual-slope A D converter memristive A D converter memristor robustness

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Data-driven real-time price-based demand response for industrial facilities energy management

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APPLIED ENERGY 2021年 283卷

作者： Lu, Renzhi Bai, Ruichang Huang, Yuan Li, Yuting Jiang, Junhui Ding, Yuemin Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China Yangzhou Univ Sch Informat Engn Yangzhou 225127 Jiangsu Peoples R China Hanyang Univ Dept Elect Syst Engn Ansan 15588 South Korea Norwegian Univ Sci & Technol Dept Energy & Proc Engn N-7034 Trondheim Norway

Recent advances in smart grid technologies have highlighted demand response (DR) as an important tool to alleviate electricity demand-supply mismatches. In this paper, a real-time price (RTP)-based DR algorithm is proposed for industrial facilities, aiming to minimize the electricity cost while satisfying production requirements. In particular, due to future price uncertainties, a data-driven approach is adopted to forecast the future unknown prices for supporting global time horizon optimization, which is realized by long short-term memory recurrent neural network (LSTM RNN). With the aid of predicted prices, the industrial facility energy management is formulated as a mixed integer linear programming (MILP) problem, which is then solved by Gurobi over a rolling horizon basis. Finally, an entire practical steel powder manufacturing process is selected as a case study to verify the RTP-based DR scheme. Numerical simulation results show that the proposed scheme is able to effectively shift energy consumption from peak to off-peak periods and reduce the electricity cost of the facility, while satisfying all of the operating constraints. The performance of the presented data driven RTP forecasting approach is compared to different prediction methods, and error sensitivity analyses are also conducted to evaluate the impact of the RTP uncertainties and the robustness of the proposed RTP-based DR algorithm. Moreover, the DR capability to RTPs is investigated.

关键词： Data-driven price forecasting Long short-term memory Recurrent neural network Real-time demand response Industrial facility energy management

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Transmission Lines Overload Alleviation: Distributed Online Optimization Approach

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IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 2021年第5期17卷 3197-3208页

作者： Ding, Li Hu, Ping Liu, Zhi-Wei Wen, Guanghui Wuhan Univ Sch Elect Engn & Automat Wuhan 430072 Peoples R China Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Minist Educ Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China Southeast Univ Sch Math Dept Syst Sci Nanjing 210096 Peoples R China

The risk of transmission lines overload in the power grid is increasing with the large-scale integration of fluctuating distributed renewable energies. Meanwhile, the requirement for accommodating more distributed resources in the future smart grids promotes the transition from the current highly centralized control structure toward a distributed one. In this article, we propose a distributed corrective control approach to mitigate line overloads in a real-time and close-loop manner. Unlike the conventional centralized approach, only simple computation and local information exchange are required to update the local corrective control action. This makes it possible to mitigate line overloads timely and adapt to the topology changes of grids. Furthermore, the introduction of system measurements and security constraints in the proposed algorithm ensures an effective and secure corrective control without new line overloads. The performance of the proposed distributed approach is demonstrated in the IEEE 14-Bus and 118-Bus systems.

关键词： Distributed control algorithm line overload multiagent system optimal power flow (OPF)

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Resilient control and Analysis for DC Microgrid System Under DoS and Impulsive FDI Attacks

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IEEE TRANSACTIONS ON SMART GRID 2021年第5期12卷 3742-3754页

作者： Liu, Xiao-Kang Wen, Changyun Xu, Qianwen Wang, Yan-Wu Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Minist Educ Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China Nanyang Technol Univ Sch Elect & Elect Engn Singapore 639798 Singapore KTH Royal Inst Technol Elect Power & Energy Syst Div S-10044 Stockholm Sweden

This paper proposes a resilient controller for DC microgrid to achieve current sharing and voltage restoration under discrete-time false data injection (FDI) and denial-of-service (DoS) attacks. Switching and impulsive signals are used to model the dynamic system of DC microgrid under DoS and FDI. To deal with the cyber attacks, a combined error of current and voltage is proposed and a switching secondary controller is designed. Based on the stability analysis method on hybrid systems, we establish a sufficient condition for selecting control parameters in relation to the average dwell time of FDI attack and the normal communication rate under DoS attack. Furthermore, an adaptive gain based control scheme is proposed to relax the requirement on knowledge of the cyber attacks in control parameter design. The utility of the results is illustrated through case studies on a tested DC microgrid.

关键词： Microgrids Voltage control Cyberattack Stability analysis Switches Matrix converters Resistance DC microgrid consensus control stability analysis cyber-attacks

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