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检索条件"任意字段=8th International Workshop on Control Engineering and Advanced Algorithms, IWCEAA 2024"

共 143 条记录，以下是31-40 订阅

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Optimizing Energy Efficiency in Smart Buildings through Intelligent HVAC control Systems 8

Optimizing Energy Efficiency in Smart Buildings Through Inte...

引用

8th international Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2024

作者： Cengiz, Korhan Biruni University Department of Electrical-Electronics Engineering Istanbul Turkey University of Jordan Faculty of Information Technology and Systems Jordan

ISBN: (纸本)9798350354423

this work explores the optimization of HVAC systems in smart buildings through the integration of advanced methodologies, including machine learning algorithms. Specif-ically, we investigate the application of neural networks, and genetic algorithms to enhance energy efficiency and user comfort. through a comprehensive experimental evaluation, we validated of our proposed approach over existing optimization strategies, as evidenced by improvements in predictive accuracy, user satisfaction, and energy consumption reduction. Our findings highlight the efficacy of leveraging advanced optimization techniques in addressing the complex challenges of HVAC control in modern building infrastructures. © 2024 IEEE.

关键词： Smart homes

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Chaotic Motion control Strategy for Gear System Based on RNN

Chaotic Motion Control Strategy for Gear System Based on RNN

引用

control engineering and advanced algorithms (iwceaa), international workshop on

作者： Xiaojuan Wei Xiaoqi Li Ningzhou Li Sixuan Qiu School of Railway Transportation Shanghai Institute of Technology Shanghai China

ISBN: (数字)9798331528881

ISBN: (纸本)9798331528898

To address the chaotic motion control problem in a single-degree-of-freedom gear system, a chaotic control method based on an external driving force controlled by a Recurrent Neural Network (RNN), optimized using the Harris Hawks Optimization (HHO) algorithm, is proposed. First, the relationship and characteristics between chaotic motion and variations in external driving forces are analyzed by bifurcation diagrams, Poincaré sections, and phase portraits, which reveal the evolution from bifurcation to chaos in the system. the temporal characteristics of the external driving force control method are explored. Acoording to this, the RNN-based chaotic controller was designed. Finally, a multi-objective optimization fitness function (MOFF) is constructed to guide the HHO algorithm optimizing the controller parameters. Simulation results demonstrate the effectiveness of the proposed control method.

关键词： Chaos Recurrent neural networks Uncertainty Gears Simulation Heuristic algorithms Force Bifurcation Motion control Optimization

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Research on Adaptive RBF Neural Network Flight control for Tilt- Rotor Quadrotor

Research on Adaptive RBF Neural Network Flight Control for T...

引用

control engineering and advanced algorithms (iwceaa), international workshop on

作者： Jiayang Qian Rui Ma Wenjing Zhou Qiang Gu School of Mechanical Engineering Jiangsu University of Technology Changzhou China

ISBN: (数字)9798331528881

ISBN: (纸本)9798331528898

Traditional multi-rotor drones are underactuated, with thrust and torque tightly coupled, making independent position and attitude control challenging. To enhance the flexibility and maneuverability of drones, this paper examines the tilt-rotor quadrotor, which offers greater agility compared to conventional quadrotors, enabling more precise control over the drone's position and attitude. We develop a mathematical model for the tilt-rotor quadrotor and utilize a control allocation matrix to linearize the nonlinear control allocation. An adaptive neural network disturbance compensation using a Global Fast Terminal Sliding Mode control algorithm (GFTSMC-RBF) is designed for the dynamics model to estimate and compensate for system uncertainties and coupling effects. the feasibility of this controller is validated through MATLAB and CoppeliaSim simulations.

关键词： Adaptation models Attitude control Heuristic algorithms Neural networks Mathematical models Resource management MATLAB Sliding mode control Quadrotors Drones

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Adaptive Sliding Mode Trajectory Tracking control of Mobile Robots

Adaptive Sliding Mode Trajectory Tracking Control of Mobile ...

引用

control engineering and advanced algorithms (iwceaa), international workshop on

作者： Tao Wu Muxia Cai Xiaodong Miao college of Mechanical and Power Engineering Nanjing Tech University Nanjing China

ISBN: (数字)9798331528881

ISBN: (纸本)9798331528898

To enhance the stability of mobile manipulators in tracking dynamic noncooperative targets within complex environments, this paper proposes an adaptive sliding mode control method. First, considering the characteristics of system nonlinearity, strong coupling effects, and gravitational influences, a dynamic model of the mobile manipulator is established using Lagrange's equations. Next, addressing the significant impact of the coupling between the chassis and the manipulator on system control and motion accuracy, an adaptive sliding mode dynamic programming trajectory tracking control strategy is designed to improve the system's balance and stability. Finally, through simulations conducted using Matlab in conjunction with the Virtual Robot Experimentation Platform (VREP), the effectiveness of the proposed control method is validated under various operating conditions.

关键词： Couplings Adaptation models Adaptive systems Trajectory tracking Mathematical models Stability analysis Trajectory Mobile robots Manipulator dynamics Sliding mode control

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State of Health Estimation for Lithium Battery via Indirect Health Factor with Gaussian Process Regression

State of Health Estimation for Lithium Battery via Indirect ...

引用

control engineering and advanced algorithms (iwceaa), international workshop on

作者： Pinzheng Tan Hailin Feng School of Mathematics and Statistics Xidian University Xi'an China

ISBN: (数字)9798331528881

ISBN: (纸本)9798331528898

To improve battery management systems's (BMS) safety and dependability, state-of-health (SOH) estimation must be done accurately. In the paper, we offer an estimating approach using differential thermal voltammetry (DTV), incremental capacity (IC), and differential thermal capacity (DTC) curves, which utilize the Gaussian Process Regression (GPR) algorithm. First, the IC, DTV, and DTC curves are smoothed using a Savitzky-Golay (SG) filter technique. Subsequently, person correlation analysis was employed to select relevant health features, which were then utilized in GPR to develop and establish the battery aging model. Finally, NASA and Oxford datasets are used to validate the estimation accuracy, robustness, and reliability of the proposed model. the results indicate that the proposed model is capable of delivering precise forecasts regarding battery health status.

关键词： thermal factors thermal engineering NASA Estimation Process control Gaussian processes Robustness Safety Root mean square Digital TV

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Low Power Consumption Optimization control of Air Conditioning for UAV Nest on Tower Based on EM Algorithm

Low Power Consumption Optimization Control of Air Conditioni...

引用

control engineering and advanced algorithms (iwceaa), international workshop on

作者： Miao Wang Junnan Liu Xiaojie Wu Wenbin Wu Jianfeng Ye State Grid Electric Power Space Technology Co. Ltd. Beijing China State Grid Fujian Electric Power Research Institute Fuzhou Fujian China

ISBN: (数字)9798331528881

ISBN: (纸本)9798331528898

Aiming at the problem of high energy consumption of air conditioning system of UAV nest on tower, a low power optimization control method based on expectation maximization (EM) algorithm is proposed. Based on the analysis of the factors affecting the temperature of the UA V nest on the tower, the air conditioning control model of the UA V nest on the tower is constructed. the operating mode of the air conditioning is dynamically adjusted using the EM algorithm, which can significantly reduce the energy consumption while ensuring the stability of the temperature inside the nest, effectively improve the energy efficiency ratio of the air conditioning system, and provide a new solution for the energy-saving operation of the UAV nest.

关键词： Air conditioning Energy consumption Heuristic algorithms Poles and towers Autonomous aerial vehicles Stability analysis Temperature control Optimization thermal stability thermal stresses

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A Domain-Level Transformation Scenario Classification Algorithm Based on Multilevel Feature Representation

A Domain-Level Transformation Scenario Classification Algori...

引用

control engineering and advanced algorithms (iwceaa), international workshop on

作者： Shen Wu Jiayin Yu Guangdong Power Grid Co. Ltd. CSG Guangzhou Guangdong China Management & Science Research Institute of Guangdong Power Grid Guangzhou Guangdong China

ISBN: (数字)9798331528881

ISBN: (纸本)9798331528898

Traditional scenarioscenario classification techniques mainly use SIFT features combined with BoW and SPM models for recognition, but this method is limited in accuracy and difficult to cope with variable scenario contents. To address this problem, this study proposes a new image scenario classification algorithm using multilevel feature representation. the algorithm constructs low-level and mid-level descriptions containing local semantics by sampling image blocks through a sliding window, extracting SIFT and CNN features, encoding them using the VLAD technique, and concatenating the features in order to form image descriptions. these descriptions are fused with the high-level semantics of the fully-connected layer to achieve the integration of local and global information and improve the accuracy of the image representation. Experiments on two commonly used datasets show that this fusion of multilevel features for image representation significantly improves the classification performance.

关键词： Accuracy Image coding control engineering Conferences Semantics Image representation Feature extraction Classification algorithms Convolutional neural networks Standards

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Facial Negative Emotion Recognition of Special Employees Based on Machine Vision

Facial Negative Emotion Recognition of Special Employees Bas...

引用

control engineering and advanced algorithms (iwceaa), international workshop on

作者： Shuai Meng Peng Liu Xue Mei Jiaxin Jiang Nanjing Tech University College of Electrical Engineering and Control Science Nanjing China

ISBN: (数字)9798331528881

ISBN: (纸本)9798331528898

With the advancement of computer vision technology, emotion recognition has become a research hotspot in recent years due to its many applications, including mental state assessment, mental illness detection, human behavior understanding, and psychological analysis. For personnel working long-term in enclosed spaces such as military bases or cabins, more subtle negative emotions may lead to unsafe behaviors, resulting in accidents. To address this issue, this paper employs an optimized MTCNN face detection algorithm and an improved Video Swin Transformer model network to detect negative emotions in such specialized personnel based on facial features. the test results show that the overall accuracy exceeds 80%, outperforming existing emotion classifiers. this greatly reduces the likelihood of safety accidents caused by emotional state-induced operational errors, providing new insights and inspiration for future research.

关键词： Training Emotion recognition Accuracy Scalability Refining Transformers Safety Classification algorithms Personnel Accidents

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A Stable control Framework for Continuous Robot-Assisted Training

A Stable Control Framework for Continuous Robot-Assisted Tra...

引用

control engineering and advanced algorithms (iwceaa), international workshop on

作者： Yaqi Zhang Rui Zou Chen Wang College of Engineering Shantou University Shantou China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (数字)9798331528881

ISBN: (纸本)9798331528898

In this paper, a control framework for an upper limb exoskeleton rehabilitation robot is proposed, emphasising the strict implementation of safety protocols to guarantee that patients in the early stages of rehabilitation can accurately follow normal human activity postures for training. First, the interpolating polynomials are optimised by considering the minimum-jerk principle in the generation of the reference trajectories required for training; then a motion-dependent function is proposed for smooth switching between two modes, normal exercise and safe stop; Finally, a non-singular terminal sliding mode (NTSM) method is proposed for accurately tracking the required joint angles, and the exoskeleton tracking error tends to be zero within a finite period of time. Furthermore, the stability of the entire system is ensured by Lyapunov stability. the simulation outcomes illustrate the efficacy and resilience of the proposed control framework.

关键词： Training Uncertainty Tracking Exoskeletons Switches Stability analysis Trajectory Safety Time factors Sliding mode control

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Adaptive PID control for Autonomous Vehicle Motor Regulation: Design and Simulation Using MATLAB

Adaptive PID Control for Autonomous Vehicle Motor Regulation...

引用

control engineering and advanced algorithms (iwceaa), international workshop on

作者： Xiaoquan Ren Kaibo Jin School of Artificial Intelligence Henan University Zhengzhou China

ISBN: (数字)9798331528881

ISBN: (纸本)9798331528898

In an autonomous driving system, the degree of control of the vehicle's speed and direction is a crucial factor in reflecting its safety and stability. Traditional PID controllers have limited performance in complex dynamic environments due to their fixed gains. To solve this problem, this paper proposes a PID control system based on an adaptive algorithm, which collects the vehicle's differential speed signal in real time, transmits it to an adaptive PID controller, and then accurately controls the motor speed through a PWM modulator. At the same time, the angle error signal generated by the motor is used to dynamically adjust the PID gains to optimize the vehicle's speed and direction control. this paper uses MATLAB's Simulink platform for simulation. the results show that the adaptive PID controller significantly shortens the adjustment time, reduces the system's oscillation phenomenon, and improves the system's stability, making it suitable for autonomous driving tasks under complex road conditions.

关键词： PI control Adaptive systems Software packages Motors Real-time systems Stability analysis PD control Vehicle dynamics MATLAB Autonomous vehicles

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