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第41届中国控制会议

作者： Fenglan Sun Xiaoshuai Wu Guoxiong Long Key Laboratory of Intelligent Analysis and Decision on Complex Systems School of ScienceChongqing University of Posts and Telecommunications Key Laboratory of Intelligent Air-Ground Cooperative Control for Universities in Chongqing College of AutomationChongqing University of Posts and Telecommunications Department of Complexity Science Potsdam Institute for Climate Impact Research

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

This paper provides an enhanced Q-learning algorithm for agent path planning in traditional grid maps,which solves the problem of agent path planning in grid *** an unknown environment,the classic Q-learning algorithm addresses the agent's path planning ***,there are several limits to this strategy in terms of path planning:the agent could only move nearby grids,and the step size is only one *** Q-learning algorithm,including changes the agent's direction and step *** action direction of agents is increased from four to *** movement step of agents is raised from one to three *** new method makes the convergence faster and proxy path ***,a set of simulation tests are presented to validate the modified Q-learning algorithm.

关键词： Agent Path planning Q-learning Grid method

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A semantic segmentation method based on improved u-net network 4

A semantic segmentation method based on improved u-net netwo...

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4th International Conference on Advanced Electronic Materials, Computers and Software Engineering, AEMCSE 2021

作者： Li, Penghui Zhang, Lijun Qiao, Jinlong Wang, Xiangguo China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex System Wuhan China

ISBN: (纸本)9781665415965

Semantic segmentation is the most important branch of image processing. Semantic segmentation based on deep learning occupies the mainstream method. CNN, FCN, U-NET and DEEPLAB series have achieved good results in the field of image semantic segmentation. The improvement methods of each network also emerge in an endless stream, but the emphasis of improving the network focuses on the feature transfer and feature fusion between network layers in each method. In this paper, based on u-net, we use deep convolution, residual autonomic force and dendrite network to improve the network model. Deep convolution can reduce the amount of calculation, deepen the depth of network, extract more abundant image information, and transmit information between network layers in a more refined way. Dendritic networks are different from ordinary neural networks. Ordinary neural networks process information as models of nerve cell bodies. The role of neural dendrites is also important in the process of information processing. Dendritic network is used as a model of neural dendrites to improve the ability of information processing. The improved network in this paper was tested on the VOC2012 dataset, and the experimental results showed that PA, mAP and IoU were 93.36%, 92.28% and 68.26% respectively. The experimental results showed that the improved network in this paper had improved in all indicators. © 2021 IEEE.

关键词： Semantic Segmentation

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Research and application of composite stochastic resonance in enhancement detection

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Chinese Physics B 2024年第1期33卷 264-273页

作者：高蕊焦尚彬薛琼婕 School of Automation and Information Engineering Xi'an University of TechnologyXi'an 710048China School of Electronic and Electrical Engineering Baoji University of Arts and SciencesBaoji 721016China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of TechnologyXi'an 710048China

Aiming at the problem that the intermediate potential part of the traditional bistable stochastic resonance model cannot be adjusted independently, a new composite stochastic resonance(NCSR) model is proposed by combining the Woods–Saxon(WS) model and the improved piecewise bistable model. The model retains the characteristics of the independent parameters of WS model and the improved piecewise model has no output saturation, all the parameters in the new model have no coupling characteristics. Under α stable noise environment, the new model is used to detect periodic signal and aperiodic signal, the detection results indicate that the new model has higher noise utilization and better detection ***, the new model is applied to image denoising, the results showed that under the same conditions, the output peak signal-to-noise ratio(PSNR) and the correlation number of NCSR method is higher than that of other commonly used linear denoising methods and improved piecewise SR methods, the effectiveness of the new model is verified.

关键词： Woods–Saxon improved piecewise model composite stochastic resonance(SR) image denoising

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Analysis of LoRa for Electronic Shelf Labels Based on Distributed Machine Learning 42

Analysis of LoRa for Electronic Shelf Labels Based on Distri...

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42nd Chinese control Conference, CCC 2023

作者： Khan, Malak Abid Ali Ma, Hongbin Jin, Ying Ma, Jingxiang Rehman, Zia Ur Rahman, Mizanur School of Automation Beijing Institute of Technology Beijing100081 China Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing100081 China

ISBN: (纸本)9789887581543

Deforestation is the primary source of global warming;traditional shelf labels use paper to display the price of the products, and human forces play a pivotal role in updating the tags where the pandemic has strictly limited its power. Various technologies provide connectivity and a fast-updating system to eliminate the paper-based approach. LoRa is one of the contenders to design the system for electronic shelf labels (ESLs). In this paper, LoRa has been used to minify data losses and guarantee the successful decoding of the carrier signals. The data parallelism at the network server (NS) is used to distribute the data packets among the gateways (GWs) for concurrent transmissions to the end devices (EDs). The EDs are placed in different ranges using machine clustering to avoid intra-SF interference and collision. The data rate (DR) and spreading factors (SFs) have been proposed to improve the performance of pure and slotted ALOHA for the properly allocated tags. The orthogonality principles follow industrial, scientific, and medical regulations (ISM) to avoid data traffic congestion. GWs under different duty cycles (DC) and bandwidth (BW) are examined to minify the network saturation and reduce the energy harvesting of the tags. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Deforestation

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Trajectory generation for quadrotor while tracking a moving target in cluttered environment

Trajectory generation for quadrotor while tracking a moving ...

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第三十九届中国控制会议

作者： Lele Xi Zhihong Peng Lei Jiao School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex System

In this paper, we present a trajectory generation method for quadrotor while tracking a moving target with relative pattern. Compared to existing methods, safe flying zone, vehicle’s physical limits and smoothness are considered to ensure obstacles avoidance and real tracking flight. To tackle with the cluttered environment, a parallel Particle Swarm Optimization algorithm is applied to calculate the safe feasible waypoints for quadrotor with consideration of target’s predicted state and the realistic tracking pattern, as well as safety. Then, a multiple waypoints constraints motion planning method is applied and embed into a cost function for solving the problem of trajectories generation and robust tracking for quadrotor via convex optimization approach, ensuring the real-time planning, with the geometrical constraint of safe flight corridor for quadrotor. The effectiveness of proposed method is verified by numerical simulation experiments.

关键词： Target tracking Trajectory generation Waypoints constraint Convex optimization

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An Approach for Upper Limb Movement Intention Recognition Using EEG and sEMG Fusion based on the MCPSA-CIIM 5

An Approach for Upper Limb Movement Intention Recognition Us...

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5th World Robot Conference Symposium on Advanced Robotics and Automation, WRC SARA 2023

作者： Zhang, Weiming Zhang, Xiaodong Xu, Cheng Zhou, Guchuan Zhang, Teng Wang, Yu Xi'an Jiaotong University Shaanxi Key Laboratory of Intelligent Robot School of Mechanical Engineering Shaanxi Xi'an China Science and Technology on Complex System Control and Intelligent Agent Cooperative Laboratory Beijing China

ISBN: (纸本)9798350307320

The upper limb motion intention recognition method based on electroencephalography (EEG) and surface electromyography (sEMG) fusion has achieved significant results in fields such as prosthetic control. However, most existing fusion methods use manual means to select features, which cannot capture temporal and spatial features at different scales, and ignore the correlation features between the two types of signals. To address these issues, this article proposes a fusion recognition method for upper limb motion intention EEG and sEMG based on Multi-scale Convolution, Polarized Self-Attention, and Cross Intelligence Integration Module. This article extracts multidimensional temporal and spatial features of EEG and sEMG through multi-scale convolution, and introduce polarized self-attention mechanism to filter the extracted multi-scale features. Simultaneously using cross enhancement strategy to extract correlation features between EEG and sEMG. Finally, the features are input into the classification network for recognition. This method was validated on the Jeong database, and the results showed that compared with CNN-LSTM and EEGNet, the recognition accuracy of this method increased by 2.63% and 3.15%, respectively. © 2023 IEEE.

关键词： Electroencephalography

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The CPG gait generate method of the quadruped robot based on iterative learning control algorithm

The CPG gait generate method of the quadruped robot based on...

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2013 2nd International Conference on Micro Nano Devices, Structure and Computing systems, MNDSCS 2013

作者： Wang, Cheng Gao, Junyao Duan, Xingguang Liu, Yi Li, Xin Xu, Zhe Sun, Wentao Intelligent Robotics Institute China Key Laboratory of Biomimetic Robots and Systems Ministry of Education China Key Laboratory of Intelligent control and decision of complex systems School of Mechatronical Engineering Beijing Institute of Technology Nandajie Zhongguancun Haidian Beijing 100081 China

ISBN: (纸本)9783037856420

Based on the quadruped robot, this paper mainly studies the two directions of the content. The first part mainly introduces the mechanical structure design and the construction of the control system of the quadruped robot, completes the prototype design of the quadruped robot based on hydraulic power system. The second part studies the CPG gait generate method of the quadruped robot based on iterative learning control algorithm. From the principle of bionics, firstly, we use the CPG principle to generate gait, and then use the iterative learning control theory to make the control more optimization. © (2013) Trans Tech Publications, Switzerland.

关键词： Learning algorithms

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A Heuristic Algorithm for Solving Resource Constrained Project Scheduling Problem with Transfer Time under Resource Bundle

A Heuristic Algorithm for Solving Resource Constrained Proje...

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第三十八届中国控制会议

作者： Junqi Cai Zhihong Peng School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex System

In this paper we investigate an extension of Resource Constrained Projected Scheduling Problem(RCPSP): the Resource Constrained Project Scheduling Problem with Transfer Time under Resource Bundle. For this complex problem, the use of a parallel scheduling scheme is proposed. Such scheme has been successfully applied to the RCPSP. Introducing transfer time and resource bundle into RCPSP causes two problems, one is the possibility of resources significantly exceed the need of a task, the other is cooperation among unfamiliar members from different team may increase the makespan of the project. In order to deal with the problem, two new concepts are developed: task-related resource weight and collaboration coefficient. Some discussion of such concepts is given of and use them for new heuristic framework we proposed. A computational test is performed and the results show that the new heuristic is very effective in finding better solutions within a very short time.

关键词： RCPSP heuristic algorithm resource bundle transfer time

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H ∞ finite time control for discrete time-varying system with interval time-varying delay

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Journal of the Franklin Institute 2018年第12期355卷 5037-5057页

作者： Menghua Chen Jian Sun School of Automation Beijing Institute of Technology Beijing 100081 China Key Laboratory of Intelligent Control and Decision of Complex System Beijing 100081 China

This paper discusses the problem of H ∞ finite time control for a discrete time-varying system with interval time-varying delay. By constructing a new augmented time-varying Lyapunov functional involving triple summation items and using discrete Wirtinger-type inequalities, delay-dependent conditions are derived, which guarantee that the closed-loop system is not only finite time bounded (FTB) but also satisfies an H ∞ performance. Furthermore, the time-varying feedback controller can be derived by solving a series of recursive linear matrix inequalities (RLMIs). Simulation results show the effectiveness and superiority of the proposed method.

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A Modified system Model and its Application on SINS/GPS Integrated system

A Modified System Model and its Application on SINS/GPS Inte...

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IEEE International Conference on Cyber Technology in Automation, control, and intelligent systems

作者： Xuan Xiao Xiang Guo Yuan Liang Chao Shi Songtian Shang Hong Hu School of Automation and State Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology

ISBN: (纸本)9781538604915

Kalman filter has been extensively applied in vast areas. However, the performance of Kalman filter rests on the accuracy of prior information such as model construction. In the integrated system of Strapdown Inertial Navigation system (SINS)/Global Positioning system (GPS), the model construction is affected by a certain error sources. The most significant one is computational errors, which are caused by improper reference frame and the absence of true values. To solve the problem, this paper presents a modified system model which reduce the impact of computational errors by selecting computational frame as reference coordinate frame and removing all true values. Simulation results have demonstrated that modified system model effectively improves the performance of Kalman filter in SINS/GPS integrated system.

关键词： Kalman filters systems modelling Integrated system strapdown inertial navigation system Error Sources Modified

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