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| 1 | Traffic Signal Timing via Deep Reinforcement Learning显示文摘In this paper, we propose a set of algorithms to design signal timing plans via deep reinforcement learning. The core idea of this approach is to set up a deep neural network(DNN) to learn the Q-function of reinforcement learning from the sampled traffic state/control inputs and the corresponding traffic system performance output. Based on the obtained DNN,we can find the appropriate signal timing policies by implicitly modeling the control actions and the change of system states.We explain the possible benefits and implementation tricks of this new approach. The relationships between this new approach and some existing approaches are also carefully discussed. | Li Li Yisheng Lv Fei-Yue Wang | 2016 | IEEE/CAA Journal of Automatica Sinica2016，3，3： | 59 |
| 2 | Where Does AlphaGo Go: From Church-Turing Thesis to AlphaGo Thesis and Beyond显示文摘An investigation on the impact and significance of the Alpha Go vs. Lee Sedol Go match is conducted, and concludes with a conjecture of the Alpha Go Thesis and its extension in accordance with the Church-Turing Thesis in the history of computing. It is postulated that the architecture and method utilized by the Alpha Go program provide an engineering solution for tackling issues in complexity and intelligence. Specifically,the Alpha Go Thesis implies that any effective procedure for hard decision problems such as NP-hard can be implemented with Alpha Go-like approach. Deep rule-based networks are proposed in attempt to establish an understandable structure for deep neural networks in deep learning. The success of Alpha Go and corresponding thesis ensure the technical soundness of the parallel intelligence approach for intelligent control and management of complex systems and knowledge automation. | Fei-Yue Wang Jun Jason Zhang Xinhu Zheng Xiao Wang Yong Yuan Xiaoxiao Dai Jie Zhang Liuqing Yang | 2016 | IEEE/CAA Journal of Automatica Sinica2016，3，2： | 44 |
| 3 | Parallel Driving in CPSS:A Unified Approach for Transport Automation and Vehicle Intelligence显示文摘The emerging development of connected and automated vehicles imposes a significant challenge on current vehicle control and transportation systems. This paper proposes a novel unified approach, Parallel Driving, a cloud-based cyberphysical-social systems(CPSS) framework aiming at synergizing connected automated driving. This study first introduces the CPSS and ACP-based intelligent machine systems. Then the parallel driving is proposed in the cyber-physical-social space,considering interactions among vehicles, human drivers, and information. Within the framework, parallel testing, parallel learning and parallel reinforcement learning are developed and concisely reviewed. Development on intelligent horizon(iHorizon)and its applications are also presented towards parallel horizon.The proposed parallel driving offers an ample solution for achieving a smooth, safe and efficient cooperation among connected automated vehicles with different levels of automation in future road transportation systems. | Fei-Yue Wang Nan-Ning Zheng Dongpu Cao Clara Marina Martinez Li Li Teng Liu | 2017 | IEEE/CAA Journal of Automatica Sinica2017，4，4： | 41 |
| 4 | A Review on Swarm Intelligence and Evolutionary Algorithms for Solving Flexible Job Shop Scheduling Problems显示文摘Flexible job shop scheduling problems(FJSP)have received much attention from academia and industry for many years.Due to their exponential complexity,swarm intelligence(SI)and evolutionary algorithms(EA)are developed,employed and improved for solving them.More than 60%of the publications are related to SI and EA.This paper intents to give a comprehensive literature review of SI and EA for solving FJSP.First,the mathematical model of FJSP is presented and the constraints in applications are summarized.Then,the encoding and decoding strategies for connecting the problem and algorithms are reviewed.The strategies for initializing algorithms?population and local search operators for improving convergence performance are summarized.Next,one classical hybrid genetic algorithm(GA)and one newest imperialist competitive algorithm(ICA)with variables neighborhood search(VNS)for solving FJSP are presented.Finally,we summarize,discus and analyze the status of SI and EA for solving FJSP and give insight into future research directions. | Kaizhou Gao Zhiguang Cao Le Zhang Zhenghua Chen Yuyan Han Quanke Pan | 2019 | IEEE/CAA Journal of Automatica Sinica2019，6，4： | 32 |
| 5 | Adaptive Sliding Mode Control for Re-entry Attitude of Near Space Hypersonic Vehicle Based on Backstepping Design显示文摘Combining sliding mode control method with radial basis function neural network(RBFNN), this paper proposes a robust adaptive control scheme based on backstepping design for re-entry attitude tracking control of near space hypersonic vehicle(NSHV) in the presence of parameter variations and external disturbances. In the attitude angle loop, a robust adaptive virtual control law is designed by using the adaptive method to estimate the unknown upper bound of the compound uncertainties. In the angular velocity loop, an adaptive sliding mode control law is designed to suppress the effect of parameter variations and external disturbances. The main benefit of the sliding mode control is robustness to parameter variations and external disturbances. To further improve the control performance, RBFNNs are introduced to approximate the compound uncertainties in the attitude angle loop and angular velocity loop, respectively. Based on Lyapunov stability theory, the tracking errors are shown to be asymptotically stable. Simulation results show that the proposed control system attains a satisfied control performance and is robust against parameter variations and external disturbances. | Jingmei Zhang Changyin Sun Ruimin Zhang Chengshan Qian | 2015 | IEEE/CAA Journal of Automatica Sinica2015，2，1： | 30 |
| 6 | The UCR Time Series Archive显示文摘The UCR time series archive–introduced in 2002,has become an important resource in the time series data mining community,with at least one thousand published papers making use of at least one data set from the archive.The original incarnation of the archive had sixteen data sets but since that time,it has gone through periodic expansions.The last expansion took place in the summer of 2015 when the archive grew from 45 to 85 data sets.This paper introduces and will focus on the new data expansion from 85 to 128 data sets.Beyond expanding this valuable resource,this paper offers pragmatic advice to anyone who may wish to evaluate a new algorithm on the archive.Finally,this paper makes a novel and yet actionable claim:of the hundreds of papers that show an improvement over the standard baseline(1-nearest neighbor classification),a fraction might be mis-attributing the reasons for their improvement.Moreover,the improvements claimed by these papers might have been achievable with a much simpler modification,requiring just a few lines of code. | Hoang Anh Dau Anthony Bagnall Kaveh Kamgar Chin-Chia Michael Yeh Yan Zhu Shaghayegh Gharghabi Chotirat Ann Ratanamahatana Eamonn Keogh | 2019 | IEEE/CAA Journal of Automatica Sinica2019，6，6： | 26 |
| 7 | Networked Control Systems:A Survey of Trends and Techniques显示文摘Networked control systems are spatially distributed systems in which the communication between sensors, actuators,and controllers occurs through a shared band-limited digital communication network. Several advantages of the network architectures include reduced system wiring, plug and play devices,increased system agility, and ease of system diagnosis and maintenance. Consequently, networked control is the current trend for industrial automation and has ever-increasing applications in a wide range of areas, such as smart grids, manufacturing systems,process control, automobiles, automated highway systems, and unmanned aerial vehicles. The modelling, analysis, and control of networked control systems have received considerable attention in the last two decades. The ‘control over networks’ is one of the key research directions for networked control systems. This paper aims at presenting a survey of trends and techniques in networked control systems from the perspective of ‘control over networks’, providing a snapshot of five control issues: sampled-data control, quantization control, networked control, event-triggered control, and security control. Some challenging issues are suggested to direct the future research. | Xian-Ming Zhang Qing-Long Han Xiaohua Ge Derui Ding Lei Ding Dong Yue Chen Peng | 2020 | IEEE/CAA Journal of Automatica Sinica2020，7，1： | 25 |
| 8 | From Parallel Plants to Smart Plants:Intelligent Control and Management for Plant Growth显示文摘Precision management of agricultural systems, aiming at optimizing profitability, productivity and sustainability,comprises a set of technologies including sensors, information systems, and informed management, etc. Expert systems are expected to aid farmers in plant management or environment control, but they are mostly based on the offline and static information, deviated from the actual situation. Parallel management,achieved by virtual/artificial agricultural system, computational experiment and parallel execution, provides a generic framework of solution for online decision support. In this paper, we present the three steps toward the parallel management of plant: growth description(the crop model), prediction, and prescription. This approach can update the expert system by adding learning ability and the adaption of knowledge database according to the descriptive and predictive model. The possibilities of passing the knowledge of experienced farmers to younger generation, as well as the application to the parallel breeding of plant through such system, are discussed. | Mengzhen Kang Fei-Yue Wang | 2017 | IEEE/CAA Journal of Automatica Sinica2017，4，2： | 25 |
| 9 | Parallel Learning:a Perspective and a Framework显示文摘The development of machine learning in complex system is hindered by two problems nowadays.The first problem is the inefficiency of exploration in state and action space,which leads to the data-hungry of some state-of-art data-driven algorithm.The second problem is the lack of a general theory which can be used to analyze and implement a complex learning system.In this paper,we proposed a general methods that can address both two issues.We combine the concepts of descriptive learning,predictive learning,and prescriptive learning into a uniform framework,so as to build a parallel system allowing learning system improved by self-boosting.Formulating a new perspective of data,knowledge and action,we provide a new methodology called parallel learning to design machine learning system for real-world problems. | Li Li Yilun Lin Nanning Zheng Fei-Yue Wang | 2017 | IEEE/CAA Journal of Automatica Sinica2017，4，3： | 25 |
| 10 | A Survey of Human-centered Intelligent Robots:Issues and Challenges显示文摘Intelligent techniques foster the dissemination of new discoveries and novel technologies that advance the ability of robots to assist and support humans. The human-centered intelligent robot has become an important research field that spans all of the robot capabilities including navigation, intelligent control, pattern recognition and human-robot interaction. This paper focuses on the recent achievements and presents a survey of existing works on human-centered robots. Furthermore, we provide a comprehensive survey of the recent development of the human-centered intelligent robot and discuss the issues and challenges in the field. | Wei He Zhijun Li C.L.Philip Chen | 2017 | IEEE/CAA Journal of Automatica Sinica2017，4，4： | 26 |
| 11 | Generative Adversarial Networks:Introduction and Outlook显示文摘Recently, generative adversarial networks(GANs)have become a research focus of artificial intelligence. Inspired by two-player zero-sum game, GANs comprise a generator and a discriminator, both trained under the adversarial learning idea.The goal of GANs is to estimate the potential distribution of real data samples and generate new samples from that distribution.Since their initiation, GANs have been widely studied due to their enormous prospect for applications, including image and vision computing, speech and language processing, etc. In this review paper, we summarize the state of the art of GANs and look into the future. Firstly, we survey GANs' proposal background,theoretic and implementation models, and application fields.Then, we discuss GANs' advantages and disadvantages, and their development trends. In particular, we investigate the relation between GANs and parallel intelligence,with the conclusion that GANs have a great potential in parallel systems research in terms of virtual-real interaction and integration. Clearly, GANs can provide substantial algorithmic support for parallel intelligence. | Kunfeng Wang Chao Gou Yanjie Duan Yilun Lin Xinhu Zheng Fei-Yue Wang | 2017 | IEEE/CAA Journal of Automatica Sinica2017，4，4： | 24 |
| 12 | An Adaptive RBF Neural Network Control Method for a Class of Nonlinear Systems显示文摘This paper focuses on designing an adaptive radial basis function neural network(RBFNN) control method for a class of nonlinear systems with unknown parameters and bounded disturbances. The problems raised by the unknown functions and external disturbances in the nonlinear system are overcome by RBFNN, combined with the single parameter direct adaptive control method. The novel adaptive control method is designed to reduce the amount of computations effectively.The uniform ultimate boundedness of the closed-loop system is guaranteed by the proposed controller. A coupled motor drives(CMD) system, which satisfies the structure of nonlinear system,is taken for simulation to confirm the effectiveness of the method.Simulations show that the developed adaptive controller has favorable performance on tracking desired signal and verify the stability of the closed-loop system. | Hongjun Yang Jinkun Liu | 2018 | IEEE/CAA Journal of Automatica Sinica2018，5，2： | 23 |
| 13 | What Does ChatGPT Say:The DAO from Algorithmic Intelligence to Linguistic Intelligence显示文摘THE well-known ancient Chinese philosopher Lao Tzu(老子)or Laozi(6th~4th century BC during the Spring and Autumn period)started his classic Tao Teh Ching《道德经》or Dao De Jing(see Fig.1)with six Chinese characters:'道(Dao)可(Ke)道(Dao)非(Fei)常(Chang)道(Dao)',which has been traditionally interpreted as“道可道,非常道”or'The Dao that can be spoken is not the eternal Dao'. | Fei-Yue Wang Qinghai Miao Xuan Li Xingxia Wang Yilun Lin | 2023 | IEEE/CAA Journal of Automatica Sinica2023，10，3： | 23 |
| 14 | Steps toward Parallel Intelligence显示文摘The origin of artificial intelligence is investigated,based on which the concepts of hybrid intelligence and parallel intelligence are presented.The paradigm shift in Intelligence indicates the 'new normal' of cyber-social-physical systems(CPSS),in which the system behaviors are guided by Merton's Laws.Thus,the ACP-based parallel intelligence consisting of Artificial societies,Computational experiments and Parallel execution are introduced to bridge the big modeling gap in CPSS. | Fei-Yue Wang Xiao Wang Lingxi Li Li Li | 2016 | IEEE/CAA Journal of Automatica Sinica2016，3，4： | 23 |
| 15 | Adaptive Fuzzy Dynamic Surface Control of Flexible-Joint Robot Systems With Input Saturation显示文摘In this paper, we propose an adaptive fuzzy dynamic surface control(DSC) scheme for single-link flexible-joint robotic systems with input saturation. A smooth function is utilized with the mean-value theorem to deal with the difficulties associated with input saturation. An adaptive DSC design with an auxiliary first-order filter is used to solve the 'explosion of complexity'problem. It is proved that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded, and the tracking error eventually converges to a small neighborhood around zero. The main advantage of the proposed method is that only one adaptation parameter needs to be updated,which reduces the computational burden significantly. Simulation results demonstrate the feasibility of the proposed scheme and the comparison results show that the improved DSC method can reduce the computational burden by almost two thirds in comparison with the standard DSC method. | Song Ling Huanqing Wang Peter X.Liu | 2019 | IEEE/CAA Journal of Automatica Sinica2019，6，1： | 22 |
| 16 | BAS-ADAM:An ADAM Based Approach to Improve the Performance of Beetle Antennae Search Optimizer显示文摘In this paper,we propose enhancements to Beetle Antennae search(BAS)algorithm,called BAS-ADAIVL to smoothen the convergence behavior and avoid trapping in localminima for a highly noin-convex objective function.We achieve this by adaptively adjusting the step-size in each iteration using the adaptive moment estimation(ADAM)update rule.The proposed algorithm also increases the convergence rate in a narrow valley.A key feature of the ADAM update rule is the ability to adjust the step-size for each dimension separately instead of using the same step-size.Since ADAM is traditionally used with gradient-based optimization algorithms,therefore we first propose a gradient estimation model without the need to differentiate the objective function.Resultantly,it demonstrates excellent performance and fast convergence rate in searching for the optimum of noin-convex functions.The efficiency of the proposed algorithm was tested on three different benchmark problems,including the training of a high-dimensional neural network.The performance is compared with particle swarm optimizer(PSO)and the original BAS algorithm. | Ameer Hamza Khan Xinwei Cao Shuai Li Vasilios N.Katsikis Liefa Liao | 2020 | IEEE/CAA Journal of Automatica Sinica2020，7，2： | 20 |
| 17 | Toward Cloud Computing QoS Architecture:Analysis of Cloud Systems and Cloud Services显示文摘Cloud can be defined as a new computing paradigm that provides scalable, on-demand, and virtualized resources for users. In this style of computing, users can access a shared pool of computing resources which are provisioned with minimal management efforts of users. Yet there are some obstacles and concerns about the use of clouds. Guaranteeing quality of service(Qo S) by service providers can be regarded as one of the main concerns for companies tending to use it. Service provisioning in clouds is based on service level agreements representing a contract negotiated between users and providers. According to this contract, if a provider cannot satisfy its agreed application requirements, it should pay penalties as compensation. In this paper, we intend to carry out a comprehensive survey on the models proposed in literature with respect to the implementation principles to address the QoS guarantee issue. | Mohammad Hossein Ghahramani MengChu Zhou Chi Tin Hon | 2017 | IEEE/CAA Journal of Automatica Sinica2017，4，1： | 19 |
| 18 | Internet of Vehicles in Big Data Era显示文摘As the rapid development of automotive telematics,modern vehicles are expected to be connected through heterogeneous radio access technologies and are able to exchange massive information with their surrounding environment. By significantly expanding the network scale and conducting both real-time and long-term information processing, the traditional Vehicular AdHoc Networks(VANETs) are evolving to the Internet of Vehicles(Io V), which promises efficient and intelligent prospect for the future transportation system. On the other hand, vehicles are not only consuming but also generating a huge amount and enormous types of data, which is referred to as Big Data. In this article, we first investigate the relationship between Io V and big data in vehicular environment, mainly on how Io V supports the transmission, storage, computing of the big data, and how Io V benefits from big data in terms of Io V characterization,performance evaluation and big data assisted communication protocol design. We then investigate the application of Io V big data in autonomous vehicles. Finally, the emerging issues of the big data enabled Io V are discussed. | Wenchao Xu Haibo Zhou Nan Cheng Feng Lyu Weisen Shi Jiayin Chen Xuemin (Sherman) Shen | 2018 | IEEE/CAA Journal of Automatica Sinica2018，5，1： | 19 |
| 19 | Fixed-time Sliding Mode Formation Control of AUVs Based on a Disturbance Observer显示文摘In this paper,we investigate formation tracking control of autonomous underwater vehicles(AUVs)with model parameter uncertainties and external disturbances.The external disturbances due to the wind,waves,and ocean currents are combined with the model parameter uncertainties as a compound disturbance.Then a disturbance observer(DO)is introduced to estimate the compound disturbance,which can be achieved within a finite time independent of the initial estimation error.Based on a DO,a novel fixed-time sliding control scheme is developed,by which the follower vehicle can track the leader vehicle with all the states globally stabilized within a given settling time.The effectiveness and performance of the method are demonstrated by numerical simulations. | Zhenyu Gao Ge Guo | 2020 | IEEE/CAA Journal of Automatica Sinica2020，7，2： | 19 |
| 20 | A Predator-prey Particle Swarm Optimization Approach to Multiple UCAV Air Combat Modeled by Dynamic Game Theory显示文摘Dynamic game theory has received considerable attention as a promising technique for formulating control actions for agents in an extended complex enterprise that involves an adversary. At each decision making step, each side seeks the best scheme with the purpose of maximizing its own objective function. In this paper, a game theoretic approach based on predatorprey particle swarm optimization(PP-PSO) is presented, and the dynamic task assignment problem for multiple unmanned combat aerial vehicles(UCAVs) in military operation is decomposed and modeled as a two-player game at each decision stage. The optimal assignment scheme of each stage is regarded as a mixed Nash equilibrium, which can be solved by using the PP-PSO. The effectiveness of our proposed methodology is verified by a typical example of an air military operation that involves two opposing forces: the attacking force Red and the defense force Blue. | Haibin Duan Pei Li Yaxiang Yu | 2015 | IEEE/CAA Journal of Automatica Sinica2015，2，1： | 19 |
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