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Urban Traffic control Meets Decision Recommendation System:A Survey and Perspective

IEEE/CAA Journal of Automatica Sinica 2024年第10期11卷 2043-2058页

作者： Qingyuan Ji Xiaoyue Wen Junchen Jin Yongdong Zhu Yisheng Lv Zhejiang Lab Hangzhou 311121China College of Engineering and Architecture Zhejiang UniversityHangzhou 310013China College of Electrical Engineering Zhejiang UniversityHangzhou 310013China the State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China IEEE

Urban traffic control is a multifaceted and demanding task that necessitates extensive decision-making to ensure the safety and efficiency of urban transportation *** approaches require traffic signal professionals to manually intervene on traffic control devices at the intersection level,utilizing their knowledge and ***,this process is cumbersome,labor-intensive,and cannot be applied on a large network *** studies have begun to explore the applicability of recommendation system for urban traffic control,which offer increased control efficiency and *** a decision recommendation system is complex,with various interdependent components,but a systematic literature review has not yet been *** this work,we present an up-to-date survey that elucidates all the detailed components of a recommendation system for urban traffic control,demonstrates the utility and efficacy of such a system in the real world using data and knowledgedriven approaches,and discusses the current challenges and potential future directions of this field.

关键词： Recommendation system traffic control traffic perception traffic prediction

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Design and experimental verification of a simplified controller for high-order converters

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INTERNATIONAL JOURNAL OF CIRCUIT THEORY AND APPLICATIONS 2023年第6期51卷 2716-2728页

作者： Zhang, Guidong Chen, Zexiang Yu, Samson S. Guangdong Univ Technol Sch Automation Guangzhou 510006 Peoples R China Minist Educ China Key Lab Syst Control & Informat Proc Shanghai 200240 Peoples R China Deakin Univ Sch Engn Melbourne Australia Guangdong Univ Technol Sch Automation Guangzhou 510006 Peoples R China

The modeling of high-order converter systems and design of their closed-loop controllers are difficult due to their high nonlinearity, hence high-order systems, large number of zero-poles, and complex frequency-domain characteristics. To ease the design methodologies, this paper studies high-order power converters and proposes a modeling and control method for such converter systems with order reduction. As an example, the 7th-order non-electrolytic capacitor-I-Z-Source converter (NEC-I-ZSC) is employed to implement the proposed design method. Operational analysis and small signal modeling of the NEC-I-ZSC are conducted, and a reduced-order controller is then devised. Experimental verification is conducted, which prove the feasibility and effectiveness of the proposed design method.

关键词： closed-loop controllers design method high-order systems reduced-order systems

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Finite-Time Model Predictive Tracking control of Position and Orientation for Redundant Manipulators

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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2023年第6期70卷 6017-6026页

作者： Jin, Long Zhang, Fan Liu, Mei Xu, Sendren Sheng-Dong Lanzhou Univ Sch Informat Sci & Engn Lanzhou 730000 Peoples R China Qinghai Normal Univ Key Lab IoT Qinghai Xining 810008 Peoples R China Natl Taiwan Univ Sci & Technol Grad Inst Automation & Control Taipei 10607 Taiwan Natl Taiwan Univ Sci & Technol Automation & Control Ctr Taipei 10607 Taiwan

Most schemes of trajectory tracking control of redundant manipulators consider only the position of the end-effector with little regard for its orientation, and reduce the feasible region of decision variables when introducing multiple levels of joint limits. To remedy these weaknesses, this article constructs a model predictive tracking control of position and orientation (MPTCPO) scheme for redundant manipulators, which is able to achieve the simultaneous control of position and orientation of the end-effector. The proposed MPTCPO scheme simultaneously minimizes the tracking error, joint-velocity norm, and joint-acceleration norm. In the meantime, it directly handles three levels of joint limits of joint angle, joint velocity, and joint acceleration without reducing the feasible region of decision variables without conversion required. In addition, a finite-time convergent neural dynamics (FTCND) model is designed to find the optimal solution of the proposed scheme. Computer simulations and physical experiments confirm the feasibility and accuracy of the proposed MPTCPO scheme solved by the FTCND model.

关键词： Manipulator dynamics End effectors Trajectory tracking Optimization Service robots Predictive models Task analysis Model predictive control (MPC) neural dynamics (ND) quadratic programming (QP) redundant manipulator simultaneous control of position and orientation

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Q-learning-based practical disturbance compensation control for hypersonic flight vehicle

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART G-JOURNAL OF AEROSPACE ENGINEERING 2023年第8期237卷 1916-1929页

作者： Li, Xu Zhang, Ziyi Ji, Yuehui Liu, Junjie Gao, Qiang Tianjin Univ Technol Sch Elect Engn & Automation Bldg 29391 Binshuixi Rd Tianjin Peoples R China Tianjin Key Lab Control Theory & Applicat Complica Tianjin Peoples R China

Aiming at the attitude control problem of hypersonic flight vehicle, a compound control strategy based on the disturbance compensation technique and Q-learning optimization is proposed. Firstly, a three-channel independent control scheme based on the super-twisting extended state observer (STESO) is proposed such that coupling among channels, uncertainties, and external disturbances can be estimated and compensated in real time. Secondly, the Q-learning mechanism is introduced to optimize the control parameters while keeping the control structure unchanged. Lastly, the convergence of the STESO is analyzed by the Lyapunov theory, and some numerical simulation results are carried out to verify the effectiveness of the proposed strategy. Compared with the traditional linear active disturbance rejection control, the proposed method can avoid a lot of manual parameter tuning process and also has better performance.

关键词： Hypersonic flight vehicle attitude control super-twisting algorithm extended state observer Q-learning

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learning anomalous human actions using frames of interest and decoderless deep embedded clustering

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INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS 2023年第10期14卷 3575-3589页

作者： Javed, Muhammad Hafeez Yu, Zeng Li, Tianrui Anwar, Noreen Rajeh, Taha M. M. Southwest Jiaotong Univ Sch Comp & Artificial Intelligence Chengdu 611756 Peoples R China Chinese Acad Sci Control Complex Syst Inst Automation State Key Lab Management Beijing Peoples R China

Inconsistent data and unclear labels make it difficult to learn anomalous behavior from video. Therefore, methods based on deep clustering are now trending in this area. A deep clustering strategy usually relies on encoding and reconstruction to facilitate information discovery. However, it seems pointless to reconstruct the input after the model's learning process is already concluded. On the other hand, multiple input types carry various features which may help identify the problem more accurately. Hence to mitigate the requirement of utilizing assorted features with clustering, we propose Skeletal Based Autoencoder (SKELBA), which allows us to process the different types of inputs parallelly. The model consists of a spatial graph convolution operator, which helps us convolve the skeletal data more precisely. A decoder-less deep clustering architecture is introduced to enhance the stability of clustering. The relation between reconstruction error and minimizing the lower bound of mutual information (MI) helps us look into decoder-free systems. The joint venture of local-global feature collection and decoder-free encoders techniques shows improved results. Extensive experiments performed on the various benchmark datasets highlight the proposed model's superiority among recently proposed approaches in the same field.

关键词： Deep learning

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Recognition of Hybrid PQ Disturbances Based on Multi-Resolution S-Transform and Decision Tree

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Energy Engineering 2023年第5期120卷 1133-1148页

作者： Feng Zhao Di Liao Xiaoqiang Chen Ying Wang School of Automation and Electrical Engineering Lanzhou Jiaotong UniversityLanzhou730070China Key Lab of Opt-Electronic Technology and Intelligent Control of Ministry of Education Lanzhou Jiaotong UniversityLanzhou730070China

Aiming at the problems of multiple types of power quality composite disturbances,strong feature correlation and high recognition error rate,a method of power quality composite disturbances identification based on multiresolution S-transform and decision tree was ***,according to IEEE standard,the signal models of seven single power quality disturbances and 17 combined power quality disturbances are given,and the disturbance waveform samples are generated in ***,in order to improve the recognition accuracy,the adjustment factor is introduced to obtain the controllable time-frequency resolution through multi-resolution S-transform time-frequency domain *** this basis,five disturbance time-frequency domain features are extracted,which quantitatively reflect the characteristics of the analyzed power quality disturbance signal,which is less than the traditional method based on ***,three classifiers such as K-nearest neighbor,support vector machine and decision tree algorithm are used to effectively complete the identification of power quality composite *** results showthat the classification accuracy of decision tree algorithmis higher than that of K-nearest neighbor and support vector ***,the proposed method is compared with other commonly used recognition *** results show that the proposedmethod is effective in terms of detection accuracy,especially for combined PQ interference.

关键词： Hybrid power quality disturbances disturbances recognition multi-resolution S-transform decision tree

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Neural Network-Based Fixed-Time Tracking and Containment control of Second-Order Heterogeneous Nonlinear Multiagent Systems

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IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2024年第8期35卷 11565-11579页

作者： Chen, Chongyang Han, Yiyan Zhu, Song Zeng, Zhigang Huazhong Univ Sci & Technol Inst Artificial Intelligence Sch Artificial Intelligence & Automation Key Lab Image Proc & Intelligent ControlMinst Edu Wuhan Peoples R China China Univ Min & Technol Sch Math Xuzhou 221116 Peoples R China

This study concentrates on the fixed-time tracking consensus and containment control of second-order heterogeneous nonlinear multiagent systems (MASs) with and without measurable velocity under directed topology. By defining a time-varying scaling function and approximating the unknown nonlinear dynamics with radial basis function neural networks (RBFNNs), a novel distributed protocol for solving the fixed-time tracking consensus and containment control problems of second-order heterogeneous nonlinear MASs with full states available is proposed based on a nonsingular sliding-mode control method constructed by designing a prescribed-time convergent sliding surface. For the scenario of immeasurable velocity, a fixed-time convergent states' observer is designed to reveal the velocity information when the unknown linearity is bounded. Subsequently, a distributed fixed-time consensus protocol based on observed velocity information is proposed for the extended results. Ultimately, the acquired results are verified by three simulation examples.

关键词： Convergence Nonlinear dynamical systems Sliding mode control Task analysis Observers Multi-agent systems Intelligent control Directed topology fixed-time consensus multiagent systems (MASs) neural networks sliding-mode control

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Fast control parameterization optimal control with improved Polak-Ribiere-Polyak conjugate gradient implementation for industrial dynamic processes

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ISA TRANSACTIONS 2022年 123卷 188-199页

作者： Liu, Ping Hu, Qingquan Li, Lei Liu, Mingjie Chen, Xiaolei Piao, Changhao Liu, Xinggao Chongqing Univ Posts & Telecommun Coll Automation Chongqing 400065 Peoples R China Zhejiang Univ Coll Control Sci & Engn State Key Lab Ind Control Technol Hangzhou 310027 Peoples R China

This paper proposes a fast control parameterization optimal control algorithm for industrial dynamic process with constraints. Derived from the frame of control variable parameterization (CVP) technique, the proposed method combines an efficient gradient computation strategy with an improved nonlinear optimization computation approach to overcome the challenge of computation efficiency caused by gradients and bounds in optimal control problems. Firstly, a fast gradient computation method based on the costate system of Hamiltonian function is developed to decrease the computational expense of gradients by employing approximate treatments and numerical integration strategy. Then, a trigonometric function transformation scheme is presented to tackle the boundary constraints so that the original optimal control problem is further converted into an unconstrained one. On this basis, an improved restricted Polak-Ribiere-Polyak (PRP) conjugate gradient approach is introduced to solve the nonlinear optimization problem by using conjugate gradient iterations and strong Wolfe line search. Meanwhile, to enhance the convergence, a restricting condition is imposed in strong Wolfe line search to create iteration step-length. Finally, the proposed algorithm is implemented on three dynamic processes. The detailed comparison among the classical CVP method, literature results and the proposed method are carried out. Simulation studies show that the proposed fast approach averagely saves more than 90% computation time in contrast to the classical CVP method, demonstrating the effectiveness of the proposed fast optimal control approach.(c) 2021 ISA. Published by Elsevier Ltd. All rights reserved.

关键词： control parameterization Optimal control PRP conjugate gradient method Fast computation Dynamic processes

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A feedforward compensation approach for cable-driven musculoskeletal systems

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ROBOTICA 2023年第4期41卷 1221-1230页

作者： Fan, Yerui Yuan, Jianbo Wu, Yaxiong Qiao, Hong Univ Sci & Technol Beijing Sch Mech Engn Beijing 100083 Peoples R China Chinese Acad Sci Inst Automation State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China

This paper presents a feedforward compensation approach for musculoskeletal systems (MSs). Compared with traditional rigid robots, human arms have the advantages of flexibility and safety in operation in unstructured environments. However, the influence of external unknown disturbances, inner friction effects, and dynamic uncertainties of the MS makes it difficult to model and practically apply. In order to reduce the inner friction effects of the hardware platform and the over-relaxation/tension of the cable-pull drive, a feedforward friction compensation method for the cable-pulled artificial muscle unit is proposed. The method analyzes the friction causes of the hardware structure and establishes a mapping network relationship between the joint variables and the muscle force error in the muscle space. The experimental results show that the method can effectively improve the control accuracy and reduce the artificial muscle over-relaxation/tension instability.

关键词： biomimetic robots control of robotic systems force control humanoid robots serial manipulator design and kinematics

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Zeno-free event-triggered fixed-time control of two-time-scale systems by Chang transformation and backstepping design

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NONLINEAR DYNAMICS 2023年第7期111卷 6379-6393页

作者： Lei, Yan Wang, Yan-Wu Liu, Xiao-Kang Yang, Wu Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automation Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China Guangxi Univ Sch Elect Engn Nanning 530004 Peoples R China

This paper investigates fixed-time stabilization of linear two-time-scale systems. The existing fixed-time control techniques are no longer applicable due to the inherent ill-conditioned numerical issues, which is induced by the time-scale separation of two-time-scale systems when carrying out stability analysis. Alternative challenge is that the considered systems are not fully actuated, such that some full rank conditions regarded to the control matrix do not hold anymore. All of these pose difficulties to the fixed-time controller design and stability analysis. To handle these issues, appropriate state transformations are proposed to decouple the system into slow and fast subsystems with approximate strict feedback structure. Then, by the backstepping method, a continuous-time controller is designed to achieve fixed-time stabilization. Furthermore, a Zeno-free event-triggered strategy is proposed to reduce the control updates and then a practical stability result of two-time-scale systems is obtained. A numerical simulation is presented to illustrate the effectiveness of the results.

关键词： Two-time-scale systems Event-triggered fixed-time stability Zeno-free dynamics Non-full actuated systems Backstepping control design

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