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Gauss-Newton unrolled neural networks and data-driven priors for regularized PSSE with robustness

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arXiv 2020年

作者： Yang, Qiuling Sadeghi, Alireza Wang, Gang Giannakis, Georgios B. Sun, Jian State Key Lab of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China Department of Electrical and Computer Engineering University of Minnesota MinneapolisMN55455 United States

Renewable energy sources, elastic loads, and purposeful manipulation of meter readings challenge the monitoring and control of today’s power systems (PS). In this context, fast and robust state estimation (SE) is timely and of major importance to maintain a comprehensive view of the system in real time. Conventional PSSE solvers typically entail minimizing a nonlinear and nonconvex least-squares cost using e.g., the Gauss-Newton method. Those iterative solvers however, are sensitive to initialization, and may converge to local minima. To overcome these hurdles, the present paper adapts and leverages recent advances on image denoising to introduce a PSSE approach with a regularizer capturing a deep neural network (DNN) prior. For the resultant regularized PSSE objective, a "Gauss-Newton-type" alternating minimization solver is developed first. To accommodate real-time monitoring, a novel end-to-end DNN is constructed subsequently by unrolling the proposed alternating minimization solver. The deep PSSE architecture can further account for the power network topology through a graph neural network (GNN) based prior. To further endow the physics-based DNN with robustness against bad data, an adversarial DNN training method is put forth. Numerical tests using real load data on the IEEE 118-bus benchmark system showcase the improved estimation and robustness performance of the proposed scheme compared with several state-of-the-art alternatives. Copyright © 2020, The Authors. All rights reserved.

关键词： Deep neural networks

A Memetic Algorithm for Curvature-Constrained Path Planning of Messenger UAV in Air-Ground Coordination

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A Memetic Algorithm for Curvature-Constrained Path Planning ...

IEEE International Conference on systems, Man and Cybernetics

作者： Yulong Ding Bin Xin Hao Zhang Jie Chen School of Automation Beijing Institute of Technology Beijing China Peng Cheng Laboratory Shenzhen China Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing China

ISBN: (数字)9781728185262

ISBN: (纸本)9781728185279

This paper addresses a UAV path planning problem for a team of cooperating heterogeneous vehicles composed of one unmanned aerial vehicle (UAV) and multiple unmanned ground vehicles (UGVs). The UGVs are used as mobile actuators and scattered in a large area. To achieve multi-UGV communication and collaboration, the UAV serves as a messenger to fly all UGVs to transmit information. The path planning of messenger UAV is formulated as a Dynamic Dubins Traveling Salesman Problem with Neighborhood (DDTSPN). A novel memetic algorithm is proposed to find the shortest route enabling the UAV to fly over all requested UGVs. In the memetic algorithm, the combination of genetic algorithm and local search is employed to find a high-quality solution in a reasonable time, and a gradient-based repair strategy is used to repair the individuals violating dynamic constraints. The calculation results on both small and large instances show that the proposed method can generate high-quality solutions as compared with the state-of-the-art algorithms.

关键词： Memetics Heuristic algorithms Maintenance engineering Traveling salesman problems Unmanned aerial vehicles Path planning Vehicle dynamics

A Quantized controller of Linear systems with Disturbances under DoS Attacks

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A Quantized Controller of Linear Systems with Disturbances u...

International Conference on control and automation (ICCA)

作者： Wenjie Liu Jian Sun Jie Chen State Key Lab of Intelligent Control and Decision of Complex Systems and School of Automation Beijing Institute of Technology Beijing China Beijing Institute of Technology Chongqing Innovation Center Chongqing China Tongji University Shanghai China

ISBN: (数字)9781728190938

ISBN: (纸本)9781728190945

This paper considers the problem of stabilizing linear time-invariant systems with quantized state measurements under both external disturbances and Denial-of-Service (DoS) attacks. An element-based impulsive controller that can stabilize systems when quantization, DoS attacks and bounded disturbances coexist is proposed. A sufficient condition for stability characterized by the parameters of DoS attacks, bit-rate and the quantizer's saturation time is obtained. Moreover, analysis shows that under an appropriate design of parameters of the controller, the resultant saturation time always remains small. A numerical example is given to confirm the validity of the proposed method.

关键词： Denial-of-service attack Quantization (signal) Encoding Decoding Bandwidth Switched systems Eigenvalues and eigenfunctions

Shaping effect of phase-locked loop on impedance characteristics of PMSG wind turbines connected to weak-grid

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Shaping effect of phase-locked loop on impedance characteris...

2020 IEEE Power and Energy Society General Meeting, PESGM 2020

作者： Wan, Feiya Li, Zhen Liu, Bin Li, Guanghui Dong, Xiaoliang Chen, Xi Yu, Samson S. Oo, Amanullah M. T. Shan, Zhenyu Liu, Xiangdong Beijing Institute of Technology School of Automation and Key Laboratory for Intelligent Control Decision on Complex Systems Beijing China China Electric Power Research Institute Beijing China State Grid Corporation of China and North China Branch of State Grid Corporation of China Beijing China GEIRI North America United States Deakin University School of Engineering 75 Pigdon Rd Waurn Ponds Victoria Australia North China University of Technology School of Electrical and Control Engineering Beijing China

ISBN: (纸本)9781728155081

With the booming installed capacity of permanent magnet synchronous generator (PMSG) for wind energy generation, the grid becomes weaker and the oscillation events are frequently observed in weak-grid-tied large-scale grid-connected PMSG wind farms. Although the impedance-based method is effective to analyze the stability of grid-connected systems, the mathematical relationship between external impedance characteristics and the internal controllers has not been quantitatively analyzed in depth, which is beneficial to the controller design. This paper studies the influence of phase-locked loop (PLL) on the impedance characteristics based on the analytical sequence impedance model of PMSG with typical topology and control structure. The shaping effect of PLL on the impedance characteristics is described so as to clearly describe the relationship between the external impedance characteristics of the wind turbines and the internal controller. Finally, the stability analysis of the grid-connected PMSG wind turbine system is provided in Matlab and simulation results are given to verify the oscillating mechanism caused by PLL. © 2020 IEEE.

关键词： Phase locked loops

Model analysis and experimental research on hydraulic high-speed impact system 8

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Model analysis and experimental research on hydraulic high-s...

8th IEEE International Conference on Fluid Power and Mechatronics, FPM 2019

作者： Wang, Shoukun Shi, Mingxin Chen, Zhihua Beijing Institute of Technolog Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing China Key Laborator Yof Servo Motion System Drive and Control Ministry of Industry and Information Technology School of Automation Beijing Institute of Technology Beijing China

ISBN: (数字)9781728103112

ISBN: (纸本)9781728103112

High-speed impact simulation test is an important test method to study the fatigue properties or limit parameters of materials. With the advantages of great impact energy, good program control and convenient test operation, hydraulic impact is widely used in high-speed impact field. A hydraulic high speed impact simulation system is designed in this paper, which uses high pressure accumulator to supply oil and converts hydraulic energy into impact energy through servo valve controlled cylinder system. This system can simulate dynamic change process of impact velocity and acceleration of projectile, and has impact angle adjustment and end buffer function. First, the composition and working principle of this hydraulic impact simulation system is introduced, as well as the analysis of the hydraulic impact mechanism. Second, the system dynamics model of servo valve controlled cylinder based on accumulator oil is built, and the simplified model and its basic characteristics are analyzed. Then, the Influences of various parameters in impact dynamic model on impact process are also discussed. Finally, the simulation system and physical prototype system of hydraulic impact is presented, the simulation and actual impact test data and corresponding analysis conclusions are also given. © 2019 IEEE.

关键词： Software testing

Resonant beam communications with echo interference elimination

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arXiv 2021年

作者： Xiong, Mingliang Liu, Qingwen Wang, Gang Giannakis, Georgios B. Zhang, Sihai Zhu, Jinkang Huang, Chuan College of Electronics and Information Engineering Tongji University Shanghai201804 China State Key Lab of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China Department of Electrical and Computer Engineering University of Minnesota MinneapolisMN55455 United States Key Lab of Wireless-Optical Communications University of Science and Technology of China Hefei Anhui230026 China School of Science and Engineering Chinese University of Hong Kong Shenzhen Guangdong518172 Hong Kong

Resonant beam communications (RBCom) is capable of providing wide bandwidth when using light as the carrier. Besides, the RBCom system possesses the characteristics of mobility, high signal-to-noise ratio (SNR), and multiplexing. Nevertheless, the channel of the RBCom system is distinct from other light communication technologies due to the echo interference issue. In this paper, we reveal the mechanism of the echo interference and propose the method to eliminate the interference. Moreover, we present an exemplary design based on frequency shifting and optical filtering, along with its mathematic model and performance analysis. The numerical evaluation shows that the channel capacity is greater than 15 bit/s/Hz. Copyright © 2021, The Authors. All rights reserved.

关键词： Internet of things

Learning Hidden Markov Models for Linear Gaussian systems with Applications to Event-based state Estimation

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arXiv 2020年

作者： Zheng, Kaikai Shi, Dawei Shi, Ling State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Kowloon Hong Kong

This work attempts to approximate a linear Gaussian system with a finite-state hidden Markov model (HMM), which is found useful in solving sophisticated event-based state estimation problems. An indirect modeling approach is developed, wherein a state space model (SSM) is firstly identified for a Gaussian system and the SSM is then used as an emulator for learning an HMM. In the proposed method, the training data for the HMM are obtained from the data generated by the SSM through building a quantization mapping. Parameter learning algorithms are designed to learn the parameters of the HMM, through exploiting the periodical structural characteristics of the HMM. The convergence and asymptotic properties of the proposed algorithms are analyzed. The HMM learned using the proposed algorithms is applied to event-triggered state estimation, and numerical results on model learning and state estimation demonstrate the validity of the proposed algorithms. Copyright © 2020, The Authors. All rights reserved.

关键词： Hidden Markov models

Graph Optimization based Visual SLAM fusing keyPoints and Markers

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Graph Optimization based Visual SLAM fusing KeyPoints and Ma...

Chinese control Conference (CCC)

作者： Zhen Chen Yang Zhou Fengdi Zhang Min Xu Xiangdong Liu Zhen Li School of Automation and Key Laboratory for Intelligent Control & Decision on Complex Systems Beijing Institute of Technology Beijing P. R. China Beijing Aerospace Automatic Control Institute P. R. China

ISBN: (数字)9789881563903

ISBN: (纸本)9781728165233

Simultaneous localization and mapping (SLAM) plays an important role in autonomous navigation for mobile robots. Most of the visual SLAM approaches use keypoints for tracking, whose performance however suffers from the unstable landmarks during task due to uncertain light condition and frequently changeable viewpoint. The situation even becomes worse for visual SLAM in low texture environment especially in indoor buildings, where the supplementary artificial markers can be used to improve the robust detection under a wider range of circumstances. Inspired by this thought, this paper developed a visual SLAM system integrated with keypoints and artificial markers. A graph optimization problem is constructed to optimize the trajectory by taking both the reprojection error of keypoints and the influence of markers into consideration. The experimental results on SPM dataset demonstrate the superior accuracy of the proposed graph optimization algorithm compared with the start-of-the-art ORB-SLAM2.

关键词： Cameras Jacobian matrices Simultaneous localization and mapping Optimization Visualization Trajectory

Distributed stochastic proximal algorithm with random reshuffling for non-smooth finite-sum optimization

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arXiv 2021年

作者： Jiang, Xia Zeng, Xianlin Sun, Jian Chen, Jie Xie, Lihua Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China Beijing Institute of Technology Chongqing Innovation Center Chongqing401120 China School of Electronic and Information Engineering Tongji University Shanghai200082 China Ministry of Education Beijing100081 China School of Electrical and Electronic Engineering Nanyang Technological University Singapore639798 Singapore

The non-smooth finite-sum minimization is a fundamental problem in machine learning. This paper develops a distributed stochastic proximal-gradient algorithm with random reshuffling to solve the finite-sum minimization over time-varying multi-agent networks. The objective function is a sum of differentiable convex functions and non-smooth regularization. Each agent in the network updates local variables by local information exchange and cooperates to seek an optimal solution. We prove that local variable estimates generated by the proposed algorithm achieve consensus and are attracted to a neighborhood of the optimal solution with an (formula presented) convergence rate, where T is the total number of iterations. Finally, some comparative simulations are provided to verify the convergence performance of the proposed algorithm. © 2021, CC BY.

关键词： Optimal systems