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16th IEEE International Conference on Computational Intelligence and Communication Networks, CICN 2024

作者： Chen, Keyang School of Computer Science Huainan Normal University Anhui Huainan232038 China

ISBN: (纸本)9798331505264

In recent years, due to the popularity of computer networks, campus wireless network security has received attention from people. The campus wireless network training security risk assessment system can collect and store real-time data services and security accident information in the campus wireless network. This article adopted intelligent control algorithm (ICA) to analyze and process the collected data, and identify potential safety hazards. This article conducted real-time monitoring of campus wireless networks and quickly responds to them. By setting different attack scenarios, this article evaluated the security of campus wireless networks using ICA and compared them with traditional methods. The detection rate based on ICA in simple attacks was 98%, while the detection rate of traditional methods was 85%. The detection rate based on ICA in moderate attacks was 95%, while the detection rate of traditional methods was 78%. The campus wireless network training security risk assessment system based on ICA helps to prevent and manage security risks, promoting harmonious development of the campus. © 2024 IEEE.

关键词： Campus Wireless Network intelligent control algorithm Security Risk Assessment Security Risks

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Optimization strategies for cost-effectiveness in piezoelectric energy harvesting systems

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INTERNATIONAL JOURNAL OF DYNAMICS AND control 2025年第4期13卷 1-15页

作者： Touairi, Souad Ghalim, Nidal Ouaomar, Hanaa Kouider, Nourreeddine Sultan Molay Slimane Univ Lab Ind Engn & Surface Engn FST Beni Mellal 23000 Morocco

This document highlighted a new approach to optimizing the cost-effectiveness of piezoelectric energy harvesting systems. The proposed method achieved the two fundamental objectives of (i) maximizing energy harvesting efficiency through optimal energy transfer to storage systems, and (ii) ensuring system stability and reliability under various mechanical stresses. For this purpose, an intelligent control algorithm has been implemented and integrated into the storage and energy management components. Further proof of concept was provided by the design and implementation of a prototype Spartan-6 board, taking advantage of advanced prototyping platforms for real-time operation and precise control. Furthermore, a comprehensive analysis, including formal evaluations, simulations and experimental tests, confirmed the system's effectiveness in improving energy harvesting performance and maintaining constant operational stability, making it a promising solution for sustainable energy applications.

关键词： Hybrid vehicle (HV) Super-capacitor (SC) intelligent control algorithm Energy storage optimization Real-time control (RTC)

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Design of intelligent Connected Cruise control With Vehicle-to-Vehicle Communication Delays

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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2022年第8期71卷 9011-9025页

作者： Wang, Zhuwei Jin, Senfan Liu, Lihan Fang, Chao Li, Meng Guo, Song Beijing Univ Technol Fac Informat Technol Beijing 100124 Peoples R China Beijing Wuzi Univ Sch Informat Beijing 101149 Peoples R China Beijing Univ Technol Fac Informat Technol Beijing 100081 Peoples R China Purple Mt Lab Networking Commun & Secur Nanjing 210096 Peoples R China Hong Kong Polytech Univ Dept Comp Hong Kong 999077 Peoples R China

Connected cruise control (CCC) refers to a type of advanced driver assistance system combined with wireless vehicle-to-vehicle (V2V) communication technology to improve control stability and driving safety. However, it is urgent to investigate intelligent control algorithms to improve the adaptability of CCC in complex traffic environment. In addition, the effect of communication delays attributed to shared wireless communications on the performance degradation of the intelligent CCC design cannot be ignored. In this study, the design of deep reinforcement learning (DRL) controller for CCC system in high-dynamic traffic scenarios is investigated, which considers both time-varying leading velocity and communication delays. To be more specific, an intelligent CCC algorithm based on deep deterministic policy gradient (DDPG) is developed. According to the training samples obtained from interacting with the traffic environment, the actor network and the critic network are trained to maximize the quadratic reward function determined by state errors and control inputs for generating intelligent control strategies. In particular, the effect of previous control strategies is considered in vehicle dynamics analysis, optimization problem formulation and Markov decision process (MDP) definition to compensate the performance degradation attributed to communication delays. Lastly, the effectiveness and convergence of the proposed DRL-based CCC controller are verified through numerical simulations with various conditions. The superior performance of the proposed algorithm is shown by comparing with existing traditional algorithms and state-of-the-art DRL algorithms.

关键词： Delays Heuristic algorithms Vehicle dynamics Cruise control Stability analysis Real-time systems Optimal control Communication delays connected cruise control dynamic traffic intelligent control algorithm

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intelligent control system of agricultural unmanned tractor tillage trajectory

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JOURNAL OF intelligent & FUZZY SYSTEMS 2020年第6期38卷 7449-7459页

作者： Yue, Guang Pan, Yutian Shanxi Police Coll Dept Publ Secur Taiyuan 030401 Peoples R China North Univ China Coll Mech & Elect Engn Taiyuan Peoples R China

As the large error and low efficiency of manual tillage, tractor tillage has become the focus of the current research. However, tractor driving requires a lot of manpower and time. Therefore, the overall efficiency of agricultural tillage is reduced. To address this problem, an intelligent control system of agricultural unmanned tractor tillage trajectory based on machine vision is proposed in this paper. First, the hardware of the automatic control system of agricultural unmanned tractor is designed. Then the intelligent control algorithm is proposed to realize the software design, and the image of tractor tillage environment is processed. Finally, the adaptive path tracking algorithm is applied to realize the adaptive tracking of the agricultural unmanned tractor tillage trajectory, so as to realize the trajectory control. Experimental results show that the designed system can accurately track and control the agricultural unmanned tractor tillage trajectory and improve tractor operation efficiency.

关键词： Machine vision unmanned agricultural tractor intelligent control algorithm

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Research on four-wheel independent steering intelligent control strategy based on minimum load

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CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE 2021年第9期33卷 e6145-e6145页

作者： Chen, Huipeng Chen, Sen Zhou, Rougang Huang, Xiaoyan Zhu, Shaopeng HangZhou DianZi Univ Sch Mech Engn Hangzhou Peoples R China Zhejiang Univ Power Machinery & Vehicular Engn Inst Coll Energy Engn Hangzhou 310058 Peoples R China

Around the new four-wheel independent steering system, the adjustment principle of Akman angle is studied in this article. In order to improve steering stability and reduce tire wear, a new algorithm for optimal Ackerman angle allocation at full speed is proposed. Furthermore, combined with the minimum load rule, the four-wheel rotation angle and driving force are optimized. In this process, Carsim vehicle model and MATLAB/Simulink force and angle allocation algorithm model are established. The final system simulation and performance evaluation demonstrate the effectiveness of the proposed force and angle distribution algorithm for vehicle stability and tire wear optimization.

关键词： Ackerman angle intelligent control algorithm minimum load steering stability tire wear

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Long tunnel lighting environment improvement method based on multiple-parameter intelligent control: Considering dynamic changes in luminance difference

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TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY 2022年 128卷

作者： Niu, Jia an Liang, Bo He, Shiyong Xiao, Jinghang Qin, Can Chongqing Jiaotong Univ State Key Lab Mt Bridge & Tunnel Engn Chongqing 400074 Peoples R China Chongqing Jiaotong Univ Sch Civil Engn Chongqing 400074 Peoples R China

The difference between luminance in design versus road surface in the lighting environment of long tunnels often results in the road surface luminance not reaching safety standards. To solve this problem, this study proposes a method to improve the lighting environment of long tunnels. First, based on field tests and mathematical sta-tistics, the main influencing factors of the luminance difference phenomenon are found to be (in descending order) the visibility level, traffic flow, interior zone luminance, and vehicle speed. Second, the relationship between tunnel visibility and road surface luminance is quantified, and the effect of luminance difference on road surface luminance is further investigated. Considering the characteristics of luminance difference, a dynamic optimization model of lighting luminance is established. Based on the typical lighting scenes of long highway tunnels, the optimization model is then integrated with two intelligent control algorithms to establish and optimize the lighting control model. Finally, based on a combination of the dynamic optimization model and intelligent control model, a method is introduced to improve the lighting environment of long tunnels, and its effectiveness is verified. The research results show that in different lighting scenes involving time periods and weather conditions, the proposed method can dynamically adjust the lighting luminance in a long tunnel to ensure that the average road surface luminance meets the safety luminance. It is shown that the safety luminance qualified rate increases by 39.58 %, 26.04 %, and 5.21 % on sunny, cloudy, and rainy days, respectively, and energy usage can be reduced by 21.59 %, 32.13 %, and 33.03 %, respectively.

关键词： Long tunnel Luminance difference phenomenon Lighting environment improvement Multiple influencing factors intelligent control algorithm

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A Programmable controller Based on CAN Field Bus Embedded Microprocessor and FPGA

A Programmable Controller Based on CAN Field Bus Embedded Mi...

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7th International Symposium on Instrumentation and control Technology

作者： Cai Qizhong Guo Yifeng Chen Wenhei Wang Mingtao Guangxi Univ Technol Liuzhou 545006 Peoples R China

ISBN: (纸本)9780819473639

One kind of new programmable controller(PLC) is introduced in this paper. The advanced embedded microprocessor and Field-Programmable Gate Array (FPGA) device are applied in the PLC system. The PLC system structure was presented in this paper. It includes 32 bits Advanced RISC Machines (ARM) embedded microprocessor as control core, FPGA as control arithmetic coprocessor and CAN bus as data communication criteria protocol connected the host controller and its various extension modules. It is detailed given that the circuits and working principle, I/O interface circuit between ARM and FPGA and interface circuit between ARM and FPGA coprocessor. Furthermore the interface circuit diagrams between various modules are written. In addition, it is introduced that ladder chart program how to control the transfer info of control arithmetic part in FPGA coprocessor. The PLC, through nearly two months of operation to meet the design of the basic requirements.

关键词： ARM programmable controller (PLC) intelligent control algorithm CAN bus FPGA

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An Automatic Parachute Separation System for Aerial Dispersal Miniature Reconnaissance Robot 28

An Automatic Parachute Separation System for Aerial Dispersa...

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28th Chinese control and Decision Conference

作者： Chen, Yao Shi, Xuanyang Beijing Inst Technol Sch Mechatron EngnMinist Educ Key Lab Intelligent Control & Decis Complex Syst Intelligent Robot InstKey Lab Biomimet Robots & 5 Nandajie Beijing 100081 Peoples R China

ISBN: (纸本)9781467397148

The kernel of the system is an intelligent control algorithm which can recognize precisely the whole dropping-process from launch module starting up to the miniature robots touching down and then determine whether the robot lands finally. The controller will activate a motor to realize the separation of parachute from the landed robot. This article, based on research into the principle of the system, proposes a control algorithm utilizing a 3-axis digital accelerometer. At last, the related experiments shows that the approach is effectual.

关键词： intelligent control algorithm recognize dropping-process separation of parachute 3-axis digital accelerometer

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Research on Three-dimensional Path Planning for Autonomous Underwater Vehicles Based on Multi Objective Decision 4

Research on Three-dimensional Path Planning for Autonomous U...

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4th International Conference on Information Science and control Engineering (ICISCE)

作者： Pan, Xin Wu, Xusheng Hou, Xinguo Feng, Yuan Naval Univ Engn Coll Elect Engn Wuhan 430033 Hubei Peoples R China

ISBN: (纸本)9781538630136

The global path planning is one of key technologies of autonomous underwater vehicle's intelligent control. For the problems as low efficiency of searching optimal solution and insufficient objectives decision in path planning in three-dimensional environment, the rule of resistance and velocity is obtained first, then a new hybrid based on genetic-ant algorithm is proposed. In the new algorithm, a new fusion strategy is put forward to improve the fusion efficiency and a comprehensive evaluation function is designed according to principles of energy, time and security. Furthermore, a method to determine the optimal path is presented by selecting the optimal paths corresponding to different velocity values. The simulation results in three-dimensional environment show that the new algorithm can converge to the optimal solution in a short time and the method to find the optimal path is feasible.

关键词： global path planning autonomous underwater vehicle intelligent control algorithm

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A new intelligent proportion integration differentiation controller using neural network

A new intelligent proportion integration differentiation con...

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International Conference on Manufacture Engineering and Environment Engineering (MEEE)

作者： Wang, Yueshan Wang, Shikui Wang, Anrong Chen, Zenghan Chongqing Three Gorges Univ Dept Elect & Informat Engn Wanzhou Peoples R China Chongqing Univ Dept Minist Educ State Key Lab High Voltage & Elect New Technol Chongqing Peoples R China

ISBN: (纸本)9781845648251;9781845648244

To the nonlinear and time-variation industrial process with uncertainties, the setting and optimization of proportion integration differentiation (PID) parameters have been always the important study topics in the automatic control field. The current optimization design methods are often difficult to consider the system requirements for quickness, reliability, and robustness. In this paper, a method of PID controller parameters optimization is presented, which is based on the combination of neural network theory with traditional PID control theory intelligent control algorithm. Then a PID controller based on control algorithm was set up and used for controlling the feeding servo system of CNC machine tool. Simulation results show that the controller can realize the online self-tuning of PID parameters according to the dynamic changes of load of the CNC system. It can achieve the precise control of the system machining parameters in a variety of conditions.

关键词： neural network intelligent control algorithm online self-tuning CNC servo system

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