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A novel modeling method of T-S fuzzy system and application

Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology 2010年第SUPPL. 1期30卷 103-106页

作者： Gao, Zhe Liao, Xiao-Zhong Sha, De-Shang School of Automation Beijing Institute of Technology Beijing 100081 China Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing 100081 China

A novel modeling method of T-S fuzzy system for an affine nonlinear system is proposed. Based on this method, the responses of T-S fuzzy system is the same as the original nonlinear, the modeling error is avoided compared with the linearization method around the equilibrium points, and this method can be applied the nonlinear system contained the multiple nonlinear terms. T-S fuzzy model of GMAW system is established, the response characteristics of the T-S fuzzy system are not changed compared with the nonlinear GMAW system. The simulation result proves the validity of this method.

关键词： Nonlinear systems

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Dynamics of Small World Effect and Random Fuzzy Graph

Research Square

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Research Square 2021年

作者： Zhang, Yijin Huang, Jie Lin, Zongbing Key Lab of Intelligent Analysis and Decision on Complex Systems Chongqing Municipal Key Laboratory of Industrial Internet of Things & Networked Control Ministry of Education Chongqing University of Posts and Telecommunications Chongqing400065 China School of Mathematics and Computer Science Panzhihua University Panzhihua617000 China

Small World Effect (or Six Degrees of Separation theory) has generated significant influence in the world. Many researchers and institutes have done lots of work on the study of it. We model Small World Effect by random process and Graph, calculate the probability that any two people i and j in the world can contact each other after n steps (forwarding messages by intermediaries) based on different R (average number of acquaintances everyone has in the world).When R=50 or 80, if, the probability is 0.848 and the search is very likely to happen. When R=150, n=4, this probability is 0.99994, that is, after 4 steps, any two people in the world will establish connection almost surely. In the sense of Dunbar's number (R=150), six degrees of separation becomes four degrees of separation. We propose the concepts of (directed) Random Fuzzy Graph for the very first time which can describe the fact of recognition among people best, because the relation among persons is random and fuzzy. © 2021, CC BY.

关键词： Random processes

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Design of a Novel Autonomous Docking system With a Supporting Robotic Fish

Design of a Novel Autonomous Docking System With a Supportin...

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IEEE International Conference on Real-time Computing and Robotics (RCAR)

作者： Huijie Dong Chunyang Zhao Tiezhu Qiao Jian Wang Di Chen Yan Meng Junzhi Yu Ministry of Education Key Laboratory of Advanced Transducers and Intelligent Control System Taiyuan University of Technology Taiyuan China Institute of Automation Laboratory of Cognitive and Decision Intelligence for Complex System Chinese Academy of Sciences Beijing China Department of Advanced Manufacturing and Robotics College of Engineering State Key Laboratory for Turbulence and Complex Systems Peking University Beijing China College of Electronics and Information Engineering Guangdong Ocean University Zhanjiang China

Underwater supporting robots serving as a relay of energy supplements and communication for other underwater equipment are promising for ocean exploration, development, and protection. This paper proposes a novel autonomous docking system centered on a designed supporting robotic fish named ‘CourierFish’. Specifically, CourierFish is capable of docking with a surface dock station for supplying itself and docking with a seafloor platform for supporting equipment in the platform. A visual navigation scheme integrating LED and ArUco markers is presented for accurate localization. The control approach for docking motion is also illustrated. Simulations and aquatic experiments are performed to verify the feasibility of the proposed docking system. The obtained results lay a solid foundation for the construction of various underwater equipment and robot networks.

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Online path planning for UAV low-altitude penetration based on an improved differential evolution algorithm

Beijing Keji Daxue Xuebao/Journal of University of Science a...

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Beijing Keji Daxue Xuebao/Journal of University of Science and Technology Beijing 2012年第1期34卷 96-101页

作者： Peng, Zhi-Hong Sun, Lin Chen, Jie School of Automation Beijing Institute of Technology Beijing 100081 China Key Lab. of the Ministry of Education of China for Complex System Intelligent Control and Decision Beijing Institute of Technology Beijing 100081 China

An improved differential evolution algorithm was proposed for solving the online path planning problem of unmanned aerial vehicle (UAV) low-altitude penetration in partially known hostile environments. The algorithm adopts von Neumann topology and improves its structure to maintain the diversity of the population, prevent the population from falling into local optima in the early evolution and speed up the convergence rate in the later evolution as well. The mutation operator of differential evolution is improved to speed up the convergence rate of the algorithm, so that the optimal solution of the multi-objective optimization problem can be found quickly;the coding method combined the absolute Cartesian coordinates with the relative polar coordinates is used to improve the searching efficiency. The simulation experiment of online path planning for UAV low-altitude penetration shows that the proposed algorithm has a better performance than the unimproved differential evolution algorithm.

关键词： Antennas

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Power system state estimation via feasible point pursuit: Algorithms and Cramér-Rao bound

arXiv

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arXiv 2017年

作者： Wang, Gang Zamzam, Ahmed S. Giannakis, Georgios B. Sidiropoulos, Nicholas D. Digital Tech. Center ECE Dept. U. of Minnesota MplsMN55455 United States State Key Lab. of Intelligent Control and Decision of Complex Systems Beijing Inst. of Tech. Beijing100081 China

Accurately monitoring the system's operating point is central to the reliable and economic operation of an electric power grid. Power system state estimation (PSSE) aims to obtain complete voltage magnitude and angle information at each bus given a number of system variables at selected buses and lines. Power flow analysis is a special case of PSSE, and amounts to solving a set of noise-free power flow equations. Physical laws dictate quadratic relationships between available quantities and unknown voltages, rendering general instances of power flow and PSSE nonconvex and NP-hard. Past approaches are largely based on gradient-type iterative procedures or semidefinite relaxation (SDR). Due to nonconvexity, the solution obtained via gradienttype schemes depends on initialization, while SDR methods do not perform as desired in challenging scenarios. This paper puts forth novel feasible point pursuit (FPP)-based solvers for power flow and PSSE, which iteratively seek feasible solutions for a nonconvex quadratically constrained quadratic programming (QCQP) reformulation of the weighted least-squares (WLS) problem. Relative to the prior art, the developed solvers offer superior performance at the cost of higher complexity. Furthermore, they converge to a stationary point of the WLS problem. As a baseline for comparing different estimators, the Cramér-Rao lower bound (CRLB) is derived for the fundamental PSSE problem in this paper. Judicious numerical tests on several IEEE benchmark systems showcase markedly improved performance of our FPPbased solvers for both power flow and PSSE tasks over popular WLS-based Gauss-Newton iterations and SDR approaches. Copyright © 2017, The Authors. All rights reserved.

关键词： State estimation

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Malaria Cell Counting Diagnosis within Large Field of View

Malaria Cell Counting Diagnosis within Large Field of View

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Proceedings of the Digital Image Computing: Technqiues and Applications (DICTA)

作者： Li-hui Zou Jie Chen Juan Zhang Narciso Garcia Education Ministry Key Laboratory of Complex System Intelligent Control and Decision School of Automation Beijing Institute of Technology Beijing China Grupo de Tratamiento de Imágenes E.T.S.I. Telecomunicación Universidad Politécnica de Madrid Madrid Spain

Malaria is one of the most serious parasitic infections of human. The accurate and timely diagnosis of malaria infection is essential to control and cure the disease. Some image processing algorithms to automate the diagnosis of malaria on thin blood smears are developed, but the percentage of parasitaemia is often not as precise as manual count. One reason resulting in this error is ignoring the cells at the borders of images. In order to solve this problem, a kind of diagnosis scheme within large field of view (FOV) is proposed. It includes three steps. The first step is image mosaicing to obtain large FOV based on space-time manifolds. The second step is the segmentation of erythrocytes where an improved Hough Transform is used. The third step is the detection of nucleated components. At last, it is concluded that the counting accuracy of malaria infection within large FOV is finer than several regular FOVs.

关键词： Diseases Strips Brightness Blood Image color analysis Image motion analysis Computer vision

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Leak point localization systerm for closed vessel based on infrared image processing

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Yi Qi Yi Biao Xue Bao/Chinese Journal of Scientific Instrument 2010年第8 SUPPL.期31卷 233-236页

作者： Zhao, Ling Wang, Tao Peng, Guangzheng Zhao, Tong Complicated System of Intelligent Control and Decision Key Lab. of Education Ministry School of Automation Beijing Institute of Technology Beijing 100081 China

In this paper, a device for closed vessel's leaking localization is introduced based on infrared image processing. After the infrared thermography captured multi-frame infrared images of the closed vessel with cooling gas, each frame of the ROI region is processed by Gauss filtering. The suspected leak points are detected by hough circle detection method after their edges in the ROI are extracted by using canny edge operator. Finally, the appearance probability of the suspected leak point is used to determine a leaking point. Experiments show that the proposed method overcomes the disadvantage of infrared image's higher level noise effectively and is able to accurately localize the leak points.

关键词： Infrared imaging

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Dual adaptive control of bimanual manipulation with online fuzzy parameter tuning

Dual adaptive control of bimanual manipulation with online f...

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IEEE International Symposium on intelligent control (ISIC)

作者： Alex Smith Chenguang Yang Hongbin Ma Phil Culverhouse Angelo Cangelosi Etienne Burdet Center for Robotics and Neural Systems Plymouth University Devon UK Key Laboratory of Autonomous System and Network Control South China University of Technology Guangzhou P. R. China State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing P. R. China Department of Bioengineering Imperial College London UK

A biomimetic controller with online adaptation of impedance and force is applied to a full kinematic and dynamic model of the Baxter bimanual robot. A set of fuzzy logic engines are proposed to infer the values of tuning gains which affect the control performance and control effort of the controller, which would conventionally be set to a static value based on expert knowledge of the controller; the aim of this being to avoid the use of arbitary values to set these values. A simulated experiment is carried out, where the Baxter robot is required to move an object through a trajectory while subjected to two different disturbance forces in four phases. The controller with fuzzy inferred control gains is compared against the same controller with fixed gains to gauge the effectiveness of the new method. Results show that fuzzy inference of control gains impart an improvement in both tracking error and control effort.

关键词： Trajectory Fuzzy logic Force Dynamics Mathematical model Manipulators

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Fast Trajectory Planning for Dubins Vehicles Under Cumulative Probability of Radar Detection

SSRN

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SSRN 2022年

作者： Li, Zhuo You, keyou Sun, Jian Song, Shiji State Key Lab of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China Department of Automation and BNRist Tsinghua University Beijing100084 China Beijing Institute of Technology Chongqing Innovation Center Chongqing401120 China

This paper studies a minimum-time trajectory planning problem under radar detection, where a Dubins vehicle aims to attack a target with a limited probability of being detected. Since the probability is accumulated along the vehicle's trajectory in an integral form, we have to address a non-convex constrained functional optimization problem. To this end, Pontryagin's minimum principle is first adopted to derive the optimality condition, based on which we obtain a set of parameterized trajectories that contains all the optimal ones. Then, fast algorithms are proposed to approximately compute a minimum-time trajectory among the set. Simulations are performed to validate the effectiveness and efficiency of the proposed planning algorithms. © 2022, The Authors. All rights reserved.

关键词： Probability

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Network Parameter Generation for One-Shot Object Detection

Network Parameter Generation for One-Shot Object Detection

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IEEE International Conference on Unmanned systems (ICUS)

作者： Kang Wang Jiajia Zhao Yang Wang Shuigeng Zhou Shanghai Key Lab of Intelligent Information Processing and School of Computer Science Fudan University Shanghai China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing Electro-Mechanical Engineer Institute Beijing China School of Information Engineering Nanchang University China

ISBN: (纸本)9781728137933

Recent object detection models have achieved satisfactory performance by deep learning with large-scale annotated datasets. However, these models often perform poorly when the training examples are not sufficient enough, especially for one-shot object detection where there is only one training example of each target class. In this paper, we propose a network parameter generation framework for effective one-shot object detection. By leveraging the semantic relationship between the source-domain and the target-domain (new classes), our framework can generate network parameters for the new classes directly. Furthermore, we develop two implementation schemes for this framework: weighting-based parameter generation and regression-based parameter generation. These two schemes use different information to construct the relationship and transfer knowledge from the source-domain to the target-domain. Experiments on the PASCAL-OSCD benchmark show that our methods can significantly boost the performance of one-shot object detection.

关键词： Object detection Detectors Head Training Feature extraction Task analysis Training data

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