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Policy iteration based Q-learning for linear nonzero-sum quadratic differential games

Science China(information Sciences) 2019年第5期62卷 195-213页

作者： Xinxing LI Zhihong PENG Li LIANG Wenzhong ZHA School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex System Information Science Academy China Electronics Technology Group Corporation

In this paper, a policy iteration-based Q-learning algorithm is proposed to solve infinite horizon linear nonzero-sum quadratic differential games with completely unknown dynamics. The Q-learning algorithm, which employs off-policy reinforcement learning(RL), can learn the Nash equilibrium and the corresponding value functions online, using the data sets generated by behavior policies. First, we prove equivalence between the proposed off-policy Q-learning algorithm and an offline PI algorithm by selecting specific initially admissible polices that can be learned online. Then, the convergence of the off-policy Qlearning algorithm is proved under a mild rank condition that can be easily met by injecting appropriate probing noises into behavior policies. The generated data sets can be repeatedly used during the learning process, which is computationally effective. The simulation results demonstrate the effectiveness of the proposed Q-learning algorithm.

关键词： adaptive dynamic programming ADP Q-learning reinforcement learning RL linear nonzerosum quadratic differential games policy iteration PI off-policy

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Fault-Tolerant Cooperative Motion Planning of Connected and Automated Vehicles at a Signal-Free and Lane-Free Intersection

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IFAC-PapersOnLine 2018年第24期51卷 60-67页

作者： Li, Bai Zhang, Youmin Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an710048 China Department of Mechanical Industrial and Aerospace Engineering Concordia University Montreal Canada

Compared with a conventional intersection, a signal-free and lane-free intersection enables the vehicles to drive more flexibly, thereby to promote the throughput and to reduce congestions. This work proposes a fault-tolerant cooperative motion planning method for a number of connected and automated vehicles (CAVs) which are passing through a signal-free and lane-free intersection. Partial loss of actuator effectiveness is considered as the fault type. Even a subtle fault may significantly affect the overall team performance. Thus correctly judging whether each faulty/healthy CAV can still achieve its original goal is impossible until a corresponding motion replanning problem turns out to be solvable or not. To maximize the completeness of the original task, we propose a parallel computation framework, wherein the fault-recovery motion replanning problems in multiple levels of task completeness are tried simultaneously. Concretely, i) each faulty/healthy CAV should accomplish its original goal; ii) only each healthy CAV is required to accomplish its original goal; and iii) all the faulty/healthy CAVs try to stop safely without the need to achieve any original goals. Problems iii), ii), and i) are ranking with increasing computational difficulty. Among all the three problems, the achievable solution to the most difficult one is implemented as the fault-recovery strategy. © 2018

关键词： Motion planning Automation Fault tolerance Vehicles Automated vehicles Co operative control connected Intersection managements Optimal controls

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Towards the Future Data Market: Reward Optimization in Mobile Data Subsidization 3rd

Towards the Future Data Market: Reward Optimization in Mobil...

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3rd EAI International Conference on 6G for Future Wireless Networks, 6GN 2020

作者： Xiong, Zehui Zhao, Jun Kang, Jiawen Niyato, Dusit Deng, Ruilong Xie, Shengli Alibaba-NTU Joint Research Institute NTU Singapore Singapore School of Computer Science and Engineering NTU Singapore Singapore Energy Research Institute NTU Singapore Singapore College of Control Science and Engineering School of Cyber Science and Technology Zhejiang University Hangzhou China Guangdong-Hong Kong-Macao Joint Laboratory for Smart Discrete Manufacturing Guangzhou China Joint International Research Laboratory of Intelligent Information Processing and System Integration of IoT Ministry of Education Guangzhou China

ISBN: (纸本)9783030639402

Mobile data subsidization launched by network operators is a promising business model to provide some economic insights on the evolving direction of the 4G/5G and beyond mobile data market. The scheme allows content providers to partly subsidize mobile data consumption of mobile users in exchange for displaying a certain amount of advertisements. The users are motivated to access and consume more content without being concerned about overage charges, yielding higher revenue to the data subsidization ecosystem. For each content provider, how to provide appropriate data subsidization (reward) competing with others to earn more revenue and gain higher profit naturally becomes the key concern in such a ecosystem. In this paper, we adopt a hierarchical game approach to model the reward optimization process for the content providers. We formulate an Equilibrium Programs with Equilibrium Constraints (EPEC) problem to characterize the many-to-many interactions among multiple providers and multiple users. Considering the inherent high complexities of the EPEC problem, we propose to utilize the distributed Alternating Direction Method of Multipliers (ADMM) algorithm to obtain the optimum solutions with fast-convergence and decomposition properties of ADMM. © 2020, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Game theory

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An improved distributed nonlinear observer for leader-following consensus via differential geometry approach

arXiv

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arXiv 2020年

作者： Xu, Haotian Wang, Jingcheng Wang, Bohui Wang, Hongyuan Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 Autonomous Systems and Intelligent Control International Joint Research Center Xi'an Technological University Xi'an Shaanxi710021 China School of Aerospace Science and Technology Xidian University Xi'an710071 China

This paper is concerned with the leader-following output consensus problem in the framework of distributed nonlinear observers. In stead of certain hypotheses on the leader system, a group of geometric conditions is put forward to develop a novel distributed observer strategy with less conservatism, thereby definitely improving the applicability of the existing results. To be more specific, the improved distributed observer can precisely handle consensus problems for some nonlinear leader systems which are invalid for the traditional strategies with the certain assumption, such as Elastic Shaft Single Linkage Manipulator (ESSLM) systems and most of first-order nonlinear systems. We prove the sufficient conditions for the exponential stability of our distributed observer's error dynamic by proposing two pioneered lemmas to show the relationship between the maximum eigenvalues of two matrices appearing in Lyapunov type matrices. Then, a partial feedback linearization method with zero dynamic proposed in differential geometry is employed to design a purely decentralized control law for the affine nonlinear multiagent system. With this advancement, the existing results can be regarded as a specific case owing to that the followers can be chosen as an arbitrary minimum phase affine smooth nonlinear system. At last, the novel distributed observer and the improved purely decentralized control law are applied in the distributed control framework to construct a closed-loop system. We also prove the stability of closed-loop system to achieve leader-following consensus, i.e., the distributed control framework is proved to satisfy certainty equivalence principle. Our method is illustrated by ESSLM system and Van der Pol system as leader. Copyright © 2020, The Authors. All rights reserved.

关键词： Feedback linearization

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Antagonism between ambient ozone increase and urbanization-oriented population migration on Chinese cardiopulmonary mortality

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The Innovation 2023年第6期4卷 48-58页

作者： Haitong Zhe Sun Junchao Zhao Xiang Liu Minghao Qiu Huizhong Shen Serge Guillas Chiara Giorio Zosia Staniaszek Pei Yu Michelle W.L.Wan Man Mei Chim Kim Robin van Daalen Yilin Li Zhenze Liu Mingtao Xia Shengxian Ke Haifan Zhao Haikun Wang Kebin He Huan Liu Yuming Guo Alexander T.Archibald lYusuf Hamied Department of Chemistry University of CambridgeCambridge CB21EWUK Department of Earth Sciences University of CambridgeCambridge CB23EQUK Department of Environmental Health and Engineering Johns Hopkins Bloomberg School of Public HealthBaltimoreMD 21205USA State Key Joint Laboratory of ESPC State Environmental Protection Key Laboratory of Sources and Control of Air Pollution ComplexSchool of EnvironmentTsinghua UniversityBejing 100084China School of Atmospheric Sciences Nanjing UniversityNanjing 210023China Department of Earth System Science Stanford UniversityStanfordCA 94305USA School of Environmental Science and Engineering Southern University of Science and TechnologyShenzhen 518p55China Department of Statistical Science University College LondonLondon WC1E 6BTUK The Alan Turing Institute London NW12DBUK School of Public Heath and Preventive Medicine Monash UniversityMelboumeVIC 3004Australia British Heart Foundation Cardiovascular Epidemiology Unit Department of Public Health and Primary CareUniversity of CambridgeCambridge CB18RNUK Heart and Lung Research Institute University of CambridgeCambridge CB20BDUK Baroelona Supercomputing Center Department of Earth Sciences08034 BarcelonaSpain School of Environmental Science and Engineering Nanjing University of Information Science and TechnologyNanjing 210044China Department of Mathematics University of CaliformiaLos AngelesLos AngelesCA 90095USA State Key Laboratory of New Ceramics and Fine Processing KeyLaboratory of Advanced Materials of Ministry of EducationSchool of Materials Science and EngineeringTsinghua UniversityBeijing 100084China Department of Engineering University of CambridgeCambridge CB21PZUK National Centre for Atmospheric Science Cambridge CB21EWUK

Everincreasing ambient ozone(O3)pollution in China has been exacerbating cardiopulmonary premature ***,the urban-rural exposure inequity has seldom been ***,we assess populationcale 03 exposure and mortality burdens between 1990 and 2019 based on integrated pollution tracking and epidemiological *** find Chinese population have been suffering from climbing 03 exposure by 4.3±2.8 ppb per decade as a result of rapid urbanization and growing prosperity of socioeconomic *** residents are broadly exposed to 9.8±4.1 ppb higher ambient O3 than the adjacent urban citizens,and thus urbaniza-tion-oriented migration compromises the exposure-associated mortality on total *** excess premature deaths attributable to longterm 03 exposure,373,500(95%uncertainty interval[U]:240,600-510,900)in 2019,is underestimated in previous studies due to ignorance of cardiovascular *** 03 pollution policy should focus more on rural population who are facing an aggravating threat of mortality risks to ameliorate environmental health injustice.

关键词： ambient urban urbanization

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Distributed Nonconvex Optimization: Gradient-free Iterations and ϵ-Globally Optimal Solution

arXiv

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arXiv 2020年

作者： He, Zhiyu He, Jianping Chen, Cailian Guan, Xinping Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China Automatic Control Laboratory ETH Zurich Zurich8092 Switzerland

Distributed optimization utilizes local computation and communication to realize a global aim of optimizing the sum of local objective functions. This article addresses a class of constrained distributed nonconvex optimization problems involving univariate objectives, aiming to achieve global optimization without requiring local evaluations of gradients at every iteration. We propose a novel algorithm named CPCA, exploiting the notion of combining Chebyshev polynomial approximation, average consensus, and polynomial optimization. The proposed algorithm is i) able to obtain ϵ-globally optimal solutions for any arbitrarily small given accuracy ϵ, ii) efficient in both zeroth-order queries (i.e., evaluations of function values) and inter-agent communication, and iii) distributed terminable when the specified precision requirement is met. The key insight is to use polynomial approximations to substitute for general local objectives, distribute these approximations via average consensus, and solve an easier approximate version of the original problem. Due to the nice analytic properties of polynomials, this approximation not only facilitates efficient global optimization, but also allows the design of gradient-free iterations to reduce cumulative costs of queries and achieve geometric convergence for solving nonconvex problems. We provide a comprehensive analysis of the accuracy and complexities of the proposed algorithm. © 2020, CC BY-NC-SA.

关键词： Polynomial approximation

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A Forest Fire Detection Method Based on a Deep Learning Approach

A Forest Fire Detection Method Based on a Deep Learning Appr...

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第30届中国过程控制会议（CPCC 2019）

作者： Honggang Yu Zhentian Jiao Youmin Zhang Jing Xin Lingxia Mu Shangbin Jiao Han Liu Ding Liu Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Department of Mechanical Industrial and Aerospace Engineering Concordia University

Forest fire detection has great practical significance in actual production and ***, many current solutions are still not reliable in practice and usually affected by many *** paper presents a forest fire detection method based on deep learning approach using aerial images taken by Unmanned Aerial Vehicles(UAVs).We train a full image fire classifier by exploiting YOLOv3, a latest fast and accurate real-time object detection algorithm using deep learning neural ***, the feature map of a certain size is obtained by feature extraction network, such as 13×*** the input image is divided into 13×13 grid ***, if the central coordinate of an object in the ground truth falls in a grid cell, the grid cell will predict the object, because each grid cell will predict a fixed number of bounding *** the largest bounding box with ground truth IOU(Intersection Over Union) is used to predict *** fire patch detector developed in this paper obtains 91% mAP(mean Average Precision) on the data sets used and the FPS(Frames Per Second) average can reach 80.

关键词： Forest fire detection YOLOv3 deep learning Unmanned Aerial Vehicle(UAV)

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An MR Safe Rotary Encoder Based on Eccentric Sheave and FBG Sensors

An MR Safe Rotary Encoder Based on Eccentric Sheave and FBG ...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Shaoping Huang Anzhu Gao Zicong Wu Chuqian Lou Yanjun Wang Guang-Zhong Yang The Institute of Medical Robotics and School of Biomedical Engineering Shanghai Jiao Tong University Shanghai China Shanghai Jiao Tong University The Key Laboratory of System Control and Information Processing Ministry of Education Shanghai China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China The Institute of Medical Robotics Shanghai Jiao Tong University Shanghai China The Imperial College London and Empa-Swiss Federal Laboratories for Materials Science and Technology

MRI-guided robotic systems are emerging platforms for minimally invasive intervention because of high positioning accuracy and excellent tissue contrast. MR safe encoders are critical components for closed-loop robotic control. This paper develops an MR safe absolute rotary encoder based on eccentric sheave and FBG sensors. The eccentric sheave transforms the rotational motion of the shaft to the bending deflection of the beam on which FBG sensors are integrated. A model is built by establishing the relationship of the kinematics of the sheave, the mechanical properties of the beam with unknown length, and the strain model of two Fiber Bragg Grating (FBG) sensors. A Pseudo-Rigid Body (PRB) 3R model is used to solve a set of constrained equations for accurate rotary encoding. A prototype is built to calibrate the parameters and validate the accuracy of the encoder and its MR compatibility. Results show that the maximum angular error is 1.6°, and the RMS error is 0.46°. MRI shows that no noticeable artifacts are observed, and the Signal to Noise Ratio (SNR) is not affected. The results demonstrate the potential of the proposed method for it to be integrated with MR safe robots with easy fabrication, compact structures, and continuous measurement.

关键词： Mechanical sensors Shafts Analytical models Kinematics Transforms Fiber gratings Robot sensing systems

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Sensorless Speed control of PMSMs based on an Improved Particle Filter

Sensorless Speed Control of PMSMs based on an Improved Parti...

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International Conference on Electrical, control and Instrumentation Engineering (ICECIE)

作者： Hai-Peng Ren Zi-Yuan Nan Jie Li Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an China Xi'an University of Technology Xi'an China

ISBN: (纸本)9781728139401

Position sensors in permanent magnet synchronous motor (PMSM) are restrained in some applications because of the space restriction and the reliability of the system. A marginalized particle filter (MPF) can used to staminate the speed of the motor by combining a Kalman filter (KF) with a particle filter (PF). In the MPF algorithm, the rotor position of the permanent magnet synchronous motor (PMSM) is represented by a set of particles, and the rotor speed associated with each particle is estimated by using the KF. The PF here is used to handle the non-Gaussianity and nonlinearity of the system. In this paper, the uniform distribution of particles is proposed to replace the traditional Gaussian distribution of particles in the PF to get better performance at the low-speed range. The motor drive system prototype is built using a TMS320F28335 digital signal processor as a controller core. The proposed improved PF is used in the sensorless speed vector control PMSM system. The experimental results show that the proposed PF with a uniform distribution of initial particles enables more accurate speed estimation in the low-speed range compared to the conventional Gaussian distribution, while increasing number of particles also helps to improve the accuracy.

关键词： particle filter sensorless motor control initial distribution Particle filters Permanent magnet synchronous machines Sensors Gaussian distribution PARTICLE DISTRIBUTION Uniform distribution position sensor particles Speed Estimation

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Support Vector Regression Modeling based Data-Driven Iterative Learning control for Czochralski Crystal Growth Process

Support Vector Regression Modeling based Data-Driven Iterati...

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第三十八届中国控制会议

作者： Junchao Ren Ding Liu Yin Wan Ni Zhang National & Local Engineering Research Center of Crystal Growth Equipment and System Integration Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing

In view of the previous Czochralski(Cz) monocrystalline silicon growth control method based on mechanism model, it is difficult to accurately reflect the nonlinear and real-time variation characteristics of crystal growth process. This paper proposes a data-driven iterative learning control method based on support vector regression, which combines crystal diameter prediction model by support vector regression(SVR) off-line training with crystal growth mechanism model, and then control the crystal diameter and output key variable information in the framework of iterative learning algorithm. Simulation results for diameter control of crystal growth process and the analysis of key variable information show that the proposed method is effective and has a fast crystal diameter learning speed, and good performances of setpoint tracking and disturbance rejection, high crystal growth speed.

关键词： Data-Driven Czochralski Monocrystalline Silicon Support Vector Regression Iterative Learning control

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