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A New Method for Deriving Weights in Group Fuzzy Analytic Hierarchy Process and Evaluation Measures

IFAC-PapersOnLine 2020年第2期53卷 7941-7946页

作者： Lin Che Yeming Zhang Jingcheng Wang Miaoshun Bai Dept. of Automation Shanghai Jiaotong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 China Shanghai Municipal Engineering Design Institute (Group) Co. Ltd. China Autonomous Systems and Intelligent Control International Joint Research Center Xi’an Technological University Xi’an Shaanxi 710021 China

The paper discusses fuzzy comparison matrices, consistency check, weight prioritization methods and weight evaluation methods in fuzzy group analytic hierarchy process. There are various methods of weight prioritization, however, they are not critically evaluated. In the paper, two measures are introduced for the evaluation of the group weights. Then, a new method is proposed to improve the process of deriving weights and use it in an application compared to another common three methods. Our results show that the new method is a good method for deriving weights of indexes.

关键词： Group Fuzzy AHP Ari-Geo Method Assessment Measure Fuzzy Consistency Check Triangular Fuzzy Number

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Diameter Detection of Silicon Single Crystal Based on Brain Storm Optimization Algorithm Hough Transform

Diameter Detection of Silicon Single Crystal Based on Brain ...

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第三十八届中国控制会议

作者： Lu Kang Ding Liu National and Local Joint 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 order to improve the speed and accuracy of silicon single crystal diameter detection, this paper proposes an ellipse detection method based on brain storm optimization algorithm Hough transform, this method uses brain storm optimization algorithm to search ellipse parameters that make the accumulator obtains the maximum value after using Hough transform, then the accurate measurement value of silicon single crystal diameter is obtained. The proposed algorithm is simulated on the complete ellipse with Gaussian white noise and silicon single crystal diameter detection engineering experiments, and the results are compared with other intelligent optimization algorithms. Experimental results show that the proposed algorithm can effectively improve the speed and accuracy of ellipse detection with Hough transform, thereby verify the feasibility and effectiveness of the proposed algorithm, and improve the speed and accuracy of silicon single crystal diameter detection.

关键词： Silicon single crystal Diameter detection Ellipse detection Brain storm optimization algorithm Hough transform

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Research on Algorithm for Model Predictive control Based on Robust Optimizition

Research on Algorithm for Model Predictive Control Based on ...

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第三十八届中国控制会议

作者： Xia Zhang Ding Liu Fei Yu National and Local Joint Engineering Research Center of Crystal Growth Equipment and System Integration Xian University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing

The practicality of model predictive control(MPC) is partially limited by its ability to solve optimization problems in real time. The robust model prediction algorithm based on linear matrix inequality is divided into online and offline parts. In order to improve the response speed and control precision of the system, the upper bound of the objective function obtained by the off-line algorithm is taken as a known quantity, and a series of large asymptotically stable invariant elliptic sets are obtained by re-optimization. The state variables can be determined-lying between two ellipsoid sets within the ellipsoid set sequence, on the basis of online measured state variables. By adding an adjacent small ellipse set, the state variables are precisely located by three ellipse sets optimization, and the system control quantity is obtained. The simulation results show that this algorithm is better than the traditional algorithm. Finally, this algorithm is applied to identify parameters of silicon single crystal thermal field temperature model and the simulation results prove its excellent ability of parameters identification.

关键词： Robust optimization Model predictive control Uncertainty Online optimization

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Measurement Method of the Least Mean Square Adaptive Filtering Parameters for Gas-solid Flow

Measurement Method of the Least Mean Square Adaptive Filteri...

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Chinese Automation Congress (CAC)

作者： A. Ruidong Xie B. Yingmin Yi C. Haichuan Yang Key Lab of Manufacturing Equipment of Shaanxi Province Xi’an University of Technology Xi’an China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of Technology Xi’an China

With regard to the unknown prior knowledge of signal noise in the parameter measurement of gas-solid flow, the present paper puts forward the AC signal processing method based on the least mean square (LMS) adaptive filtering. In addition, the floating processor DSP-TMS320F28335 is employed to collect AC signal of electrostatic sensors and the acquired signals are processed by the aid of LMS adaptive filtering algorithm which adjusts the filter weights according to the criterion of the least mean square error to achieve the optimal filtering. Drawing on the experimental platform, the solid-phase velocity is measured online in real time for the gas-solid flow. The results show that the method can improve the accuracy and stability for the velocity measurement of gas-solid flow.

关键词： Filtering Velocity measurement Filtering algorithms Adaptive filters Solids Atmospheric measurements Particle measurements

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Evasion strategies of a three-player lifeline game

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Science China(information Sciences) 2018年第11期61卷 144-154页

作者： Fan ZHANG 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

This study examines a multi-player pursuit-evasion game, more specifically, a three-player lifeline game in a planar environment, where a single evader is tasked with reaching a lifeline prior to capture. A decomposition method based on an explicit policy is proposed to address the game qualitatively from two main aspects:(1) the evader's position distribution to guarantee winning the game(i.e., the escape zone),which is based on the premise of knowing the pursuers' positions initially, and(2) evasion strategies in the escape zone. First, this study decomposes the three-player lifeline game into two two-player sub-games and obtains an analytic expression of the escape zone by constructing a barrier, which is an integration of the solutions of two sub-games. This study then explicitly partitions the escape zone into several regions and derives an evasion strategy for each region. In particular, this study provides a resultant force method for the evader to balance the active goal of reaching the lifeline and the passive goal of avoiding capture. Finally,some examples from a lifeline game involving more than one pursuer are used to verify the effectiveness and scalability of the evasion strategies.

关键词： lifeline game three-player pursuit-evasion game barrier evasion strategy game of kind

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Trajectory optimisation design of robot based on artificial intelligence algorithm

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International Journal of Wireless and Mobile Computing 2019年第1期16卷 35-40页

作者： Huang, Li Zhang, Kai Hu, Wei Li, Chengcheng College of Computer Science and Technology Wuhan University of Science and Technology Hubei Wuhan430081 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Hubei Wuhan430081 China Key Laboratory of Metallurgical Equipment and Control Technology Ministry of Education Wuhan University of Science and Technology Hubei Wuhan430081 China

Artificial intelligence has attracted more and more attention and has been widely used in all walks of life, especially in the education industry;artificial intelligence has gradually become the core. Aiming at the problem of robot trajectory planning in artificial intelligence, this paper applies the project teaching method to the course of artificial intelligence, regards trajectory planning as a project, analyses and studies it, uses ant colony algorithm to find the optimal planning path. Through the teaching of the project, the students will understand the ant colony algorithm more deeply. The algorithm is programmed independently to achieve the final trajectory optimisation. Students become the main body of the classroom, give full play to the initiative and enthusiasm of the students, through the operation of the project to train the students' innovative ability and cooperation ability, and improve the overall quality of the college students. Copyright © 2019 Inderscience Enterprises Ltd.

关键词： Students

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

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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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Multi-carrier Differential Chaos Shift keying Wireless Communication Based On Chaotic Shape-forming Filter

Multi-carrier Differential Chaos Shift Keying Wireless Commu...

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Chinese Automation Congress (CAC)

作者： Hai-Peng Ren Si-Long Guo Chao Bai Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of Technology Xi’an China School of Mechatronic Engineering Xi’an Technological University Xi’an China

In recent years, chaotic communication has shown advantages, such as used the simplest matched filter to make signal-to-noise ratio (SNR) maximization and improve the resistance to multi-path interference. The chaotic shape-forming filter (CSF) has been proposed to generate the chaotic baseband signal in the wireless communication, the additional advantage of the chaotic shape-forming filter is able to generate the chaotic signal as spread sequence in Differential Chaotic Shift key (DCSK), which encodes information in the sequence. In this paper, the chaotic signal generated by CSF is used in DCSK and combined with multi-carrier frequency to improve the bit transmission rate. Because of CSF used, it helps to improve both Bit Error Rate (BER) performance and provide an additional information flow in the spread sequence itself. Simulation results indicate that the proposed method is superior to other methods over the Addition White Gaussian Noise (AWGN) channel and wireless channel.

关键词： Chaotic communication Signal to noise ratio Wireless communication Simulation Demodulation Data communication

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

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

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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

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Optimization of Missile Path Planning Based on APMO-HV Algorithm

Optimization of Missile Path Planning Based on APMO-HV Algor...

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2019 IEEE International Conference on Unmanned systems, ICUS 2019

作者： Zhang, Hu Wang, Shuai Liu, Tonglin Zhou, Aimin Zhang, Yi Beijing Electro-mechanical Engineering Institute Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China Changzhou University School of Mechanical Engineering Changzhou China East China Normal University Shanghai Key Laboratory of Multidimensional Information Processing School of Computer Science and Technology Shanghai China

ISBN: (纸本)9781728137926

In this paper, with considerations of low efficiency of missile path planning (MPP) by traditional aggregation technology, it uses affinity propagation based multi-objective evolutionary algorithm with hypervolume environment selection (APMO-HV) to solve the problem of MPP after establishing the MPP model. The experimental part compares and analyzes APMO-HV with six state-of-the-art algorithms, and applies it to address the MPP problem. The experimental results show that compared with the other six algorithms, APMO-HV has achieved the best solution performance in both the GLT test suite and MPP problem. This not only validates the effect of the proposed algorithm, but also enriches and improves the research results of MPP. © 2019 IEEE.

关键词： Evolutionary algorithms

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