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Global and Asymptotically Efficient Localization from Range Measurements

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arXiv 2022年

作者： Zeng, Guangyang Mu, Biqiang Chen, Jiming Shi, Zhiguo Wu, Junfeng The College of Control Science and Engineering The State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou310027 China Key Laboratory of Systems and Control Institute of Systems Science Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China The College of Information Science and Electronic Engineering Zhejiang University Hangzhou310027 China The School of Data Science Chinese University of Hong Kong Shenzhen Shenzhen China The State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou China

We consider the range-based localization problem, which involves estimating an object's position by using m sensors, hoping that as the number m of sensors increases, the estimate converges to the true position with the minimum variance. We show that under some conditions on the sensor deployment and measurement noises, the LS estimator is strongly consistent and asymptotically normal. However, the LS problem is nonsmooth and nonconvex, and therefore hard to solve. We then devise realizable estimators that possess the same asymptotic properties as the LS one. These estimators are based on a two-step estimation architecture, which says that any √m-consistent estimate followed by a one-step Gauss-Newton iteration can yield a solution that possesses the same asymptotic property as the LS one. The keypoint of the two-step scheme is to construct a √mconsistent estimate in the first step. In terms of whether the variance of measurement noises is known or not, we propose the Bias-Eli estimator (which involves solving a generalized trust region subproblem) and the Noise-Est estimator (which is obtained by solving a convex problem), respectively. Both of them are proved to be √m-consistent. Moreover, we show that by discarding the constraints in the above two optimization problems, the resulting closed-form estimators (called Bias-Eli-Lin and Noise-Est-Lin) are also √m-consistent. Plenty of simulations verify the correctness of our theoretical claims, showing that the proposed two-step estimators can asymptotically achieve the Cramer-Rao lower bound. Copyright © 2022, The Authors. All rights reserved.

关键词： Spurious signal noise

Autonomous Mobile Robot Navigation using Adaptive Neuro Fuzzy Inference System

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Autonomous Mobile Robot Navigation using Adaptive Neuro Fuzz...

2022 International Conference on Innovations and Development of Information Technologies and Robotics, IDITR 2022

作者： Haider, Muhammad Husnain Ali, Hub Khan, Abdullah Aman Zheng, Hao Bhutta, M. Usman Maqbool Usman, Shaban Zhi, Pengpeng Wang, Zhonglai University of Electronic Science and Technology of China Chengdu China Yangtze Delta Region Institute Huzhou China Casia State Key Laboratory for Management & Control of Complex Systems Beijing China Sichuan Artificial Intelligence Research Institute Yibin China The Chinese University of Hong Kong Robotics Lab Mae Hong Kong

ISBN: (纸本)9781665409322

Navigation of autonomous robots in unknown and cluttered environments lies among the marked trends in robotics. Unlike animals and humans, the collision-free movement of a robot is challenging and requires processing complex information. An autonomous robot needs to cope with a large amount of uncertainty while navigating. The previous methods have limitations, such as lacking obstacle avoidance behaviour, having a large number of governing rules, designing a separate controller for each navigation and obstacle avoidance, not considering the robot's dynamics, computationally expensive training, and poor performance in a cluttered environment. This paper proposes a method that comprises a single adaptive neuro fuzzy inference system (ANFIS) based controller with 16 rules compared to hundred of rules used by previous methods to address such problems. Our method takes heading angle along with distance sensors data as input. AU the inputs are fuzzified into linguistic variables such as near-far and left-right. Additionally, a fuzzy inference system (FIS) is designed and trained using the generated dataset for optimum performance of ANFIS. The proposed method efficiently provides collision-free navigation of the mobile robot in densely cluttered environments. Comprehensive experiments are performed to prove the robustness and potency of the proposed ANFIS controller. Moreover, the performance of the proposed method is compared with various previous methods. The results of these comparisons indicate our proposed method's superiority in finding a near-optimal path. © 2022 IEEE.

关键词： Navigation

Network-Constrained Unit Commitment with Flexible Temporal Resolution

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arXiv 2024年

作者： Yu, Zekuan Zhong, Haiwang Ruan, Guangchun Yan, Xinfei The State Key Laboratory of Power System Operation and Control Dept. of Electrical Engineering Tsinghua University Beijing China The Sichuan Energy Internet Research Institute Tsinghua University China The Lab for Information & Decision Systems Massachusetts Institute of Technology Massachusetts United States

Modern network-constrained unit commitment (NCUC) bears a heavy computational burden due to the ever-growing model scale. This situation becomes more challenging when detailed operational characteristics, complicated constraints, and multiple objectives are considered. We propose a novel simplification method to determine the flexible temporal resolution for acceleration and near-optimal solutions. The flexible temporal resolution is determined by analyzing the impact on generators in each adaptive time period with awareness of congestion effects. Additionally, multiple improvements are employed on the existing NCUC model compatible with flexible temporal resolution to reduce the number of integer variables while preserving the original features. A case study using the IEEE 118-bus and the Polish 2736-bus systems verifies that the proposed method achieves substantial acceleration with low cost variation and high accuracy. Copyright © 2024, The Authors. All rights reserved.

关键词： Energy management

SWDPM: A Social Welfare-Optimized Data Pricing Mechanism

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arXiv 2023年

作者： Yu, Yi Yao, Shengyue Wang, Fei-Yue Li, Juanjuan Lin, Yilun Urban Computing Lab Shanghai AI Laboratory Shanghai China The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China The Macau Institute of Systems Engineering Macau University of Science and Technology China

Data trading has been hindered by privacy concerns associated with user-owned data and the infinite reproducibility of data, making it challenging for data owners to retain exclusive rights over their data once it has been disclosed. Traditional data pricing models relied on uniform pricing or subscription-based models. However, with the development of Privacy-Preserving Computing techniques, the market can now protect the privacy and complete transactions using progressively disclosed information, which creates a technical foundation for generating greater social welfare through data usage. In this study, we propose a novel approach to modeling multi-round data trading with progressively disclosed information using a matchmaking-based Markov Decision Process (MDP) and introduce a Social Welfare-optimized Data Pricing Mechanism (SWDPM) to find optimal pricing strategies. To the best of our knowledge, this is the first study to model multi-round data trading with progressively disclosed information. Numerical experiments demonstrate that the SWDPM can increase social welfare 3 times by up to 54% in trading feasibility, 43% in trading efficiency, and 25% in trading fairness by encouraging better matching of demand and price negotiation among traders. Copyright © 2023, The Authors. All rights reserved.

关键词： Markov processes

Toward Consistent drift-free visual inertial localization on keyframe based map

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arXiv 2021年

作者： Zhang, Zhuqing Jiao, Yanmei Huang, Shoudong Wang, Yue Xiong, Rong State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Zhejiang China Centre for Autonomous Systems Faculty of Engineering and Information Technology University of Technology Sydney UltimoNSW2007 Australia

Global localization is essential for robots to perform further tasks like navigation. In this paper, we propose a new framework to perform global localization based on a filter-based visual-inertial odometry framework MSCKF. To reduce the computation and memory consumption, we only maintain the keyframe poses of the map and employ Schmidt-EKF to update the state. This global localization framework is shown to be able to maintain the consistency of the state estimator. Furthermore, we introduce a re-linearization mechanism during the updating phase. This mechanism could ease the linearization error of observation function to make the state estimation more precise. The experiments show that this mechanism is crucial for large and challenging scenes. Simulations and experiments demonstrate the effectiveness and consistency of our global localization framework. Copyright © 2021, The Authors. All rights reserved.

关键词： state estimation

Asynchronous L1-gain Filtering of Nonlinear Positive Semi-Markov Jump systems with Time-varying Delays

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Asynchronous L1-gain Filtering of Nonlinear Positive Semi-Ma...

第41届中国控制会议

作者： Chao Ma Hang Fu Yidao Ji Wei Wu School of Mechanical Engineering University of Science and Technology State Key Lab of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences

In this paper,the L-gain based filtering problem for nonlinear positive semi-Markov jump systems is investigated by proposing a novel asynchronous design *** precisely,the mode-dependent filters are designed in terms of practical observed modes instead of true system modes,such that less conservatism can be *** addition,the effect of time-varying delays is taken into account for more robustness and *** selecting suitable stochastic Lyapunov-Krasovskii functions and applying the linear programming method,sufficient conditions are established to fulfill the desired L-gain ***,the illustrative simulation is performed to verify the effectiveness of our developed control scheme.

关键词： Positive semi-Markov jump systems nonlinear semi-Markov jump systems asynchronous filtering L1-gain

Capacity Estimation of Lithium-ion Battery based on Electrochemical Model with Electrolyte Dynamics ⁎

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IFAC-PapersOnLine 2020年第2期53卷 5909-5914页

作者： Guangwei Chen Zhitao Liu Hongye Su State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou 310027 China

The remaining capacity of a battery is a crucial indicator, which has significant impact on state of Charge (SoC) estimation and the safe operations of electric vehicles. In this paper, an electrochemical model considering the electrolyte dynamics is proposed to estimate the real capacity of a lithium-ion battery. The electrochemical model with electrolyte dynamics governed by several partial differential equations has the potential to accurately describe varieties of phenomenons inside the battery. Furthermore, a Pade’ one-order approximation is adopted to obtain the transfer function between the boundary lithium-ion concentration and input current, then a boundary state estimator is proposed to estimate the the boundary lithium-ion concentration. After that, the least square method is used to obtain the adaptive update law for maximum concentration estimation in anode. Finally, the correctness of the aforementioned estimation methods is verified through simulation.

关键词： lithium-ion battery electrochemical model capacity electrolyte dynamics Pade’ approximation least square method

Driving Performance Analysis for Connected Vehicle Platoons: Velocity Perturbation and Fuel Consumption

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Driving Performance Analysis for Connected Vehicle Platoons:...

IEEE International Conference on Unmanned systems (ICUS)

作者： Yihan Zhao Xuting Duan Jianshan Zhou Long Zhang State Key Lab of Intelligent Transportation System Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control School of Transportation Science and Engineering Beihang University Beijing China State Key Lab of Intelligent Transportation System Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control Zhongguancun Laboratory School of Transportation Science and Engineering Beihang University Beijing China National Key Laboratory of Science and Technology on Information System Security Institute of Systems Engineering Beijing China

Vehicle platoon is one of the concrete manifestations of multi-vehicle cooperative control and intelligent transportation. However, the velocity perturbation in the driving process will bring about stability and safety problems. The connected autonomous vehicles (CAVs) can obtain the motion status of the lead vehicle in real time and respond to it in time, which is of far-reaching significance to platoon control. Based on this, this paper focuses on the longitudinal driving strategy of connected autonomous vehicle platoons. Specifically, we provide a discrete double-integral model controller for each vehicle in a generic scenario, and the controller performs acceleration and deceleration control at each timeslot according to the state of the vehicle in front and its own state. Simulation experiments are designed by varying the size of the platoon and the number of connected autonomous vehicles. The experimental results show that the introduction of connected autonomous vehicles can effectively suppress the platoon velocity perturbation, increase the stability of the platoon driving, and significantly reduce the fuel consumption at the same time.

关键词：

Solving Environment Economic Power Dispatch Problemroblems by Multi-objective Modified Seagull Optimization Algori Algorithm with Novel Constraint Treatments

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IAENG International Journal of Applied Mathematics 2023年第1期53卷

作者： Chen, Gonggui Tan, Tao Xiang, Wei Guan, Zhenqi Tan, Hao Yu, Jianbo Long, Hongyu Key Laboratory of Industrial Internet of Things and Networked Control Ministry of Education Chongqing University of Posts and Telecommunications Chongqing400065 China Chongqing University of Posts and Telecommunications Chongqing400065 China Economic and Technology Research Institute State Grid Chongqing Electric Power Company Chongqing401120 China Key Laboratory of Complex Systems and Bionic Control Chongqing University of Posts and Telecommunications Chongqing400065 China

In this paper, a multi-objective modified seagull optimization algorithm (MOMSOA) is proposed to handle multi-objective environmental economic power dispatch (EED) problems. The algorithm utilizes logistic map to randomize the parameter u, which increases the diversity of the algorithm and speeds up the convergence rate. Besides, the mutation operator is combined to enlarge the range of the search and to avoid falling into the local optimum. The exploration as well as exploitation capabilities for MOSOA are balanced by non-linearizing the original linear parameter A through a cosine dynamic variation strategy. Furthermore, with the assistance of a unique constraint handling approach and non-inferior sorting, MOMSOA can obtain a set of uniform Pareto optimal solution (POS). In order to verify the effectiveness of MOMSOA, experiments were conducted on diverse test systems including IEEE30-Bus, IEEE57-Bus and IEEE118-Bus test systems. During the experimental process, MOSOA and MOPSO/MODE are compared with MOMSOA. Eight trials were conducted, and optimized objective functions include fuel cost, fuel cost with valve point effect, power loss and pollution emission. The results of experiments demonstrate that the proposed MOMSOA can obtain more uniform Pareto fronts (PFs) and optimal best compromise solution (BCS). Finally, two metrics that measure the performance of multi-objective algorithms, SP and HV, are employed to evaluate the results of each algorithm, and the results reveal that solutions obtained by MOMSOA are the most uniform, with the broadest diversity and the best convergence. © 2023, IAENG International Journal of Applied Mathematics. All Rights Reserved.

关键词： Constraint handling