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检索条件"任意字段=2023 6th International Conference on Advanced Algorithms and Control Engineering, ICAACE 2023"

共 292 条记录，以下是201-210 订阅

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Events-Based Model Predictive control for Polytopic Uncertain Systems Under False Data Injection Attacks

Events-Based Model Predictive Control for Polytopic Uncertai...

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Industrial Cyber-Physical Systems (ICPS)

作者： Fan Wei Chaoling Zhangabc Xiongbo Wan School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China

In this paper, the events-based model predictive control (MPC) problem is studied for systems under false data injection (FDI) attacks. A time-varying event-triggered mechanism (ETM) is proposed to manage measurement data packet releases and a static ETM is used to reduce the influence of the FDI attacks on the controller. By using the properties of the defined robust positive invariant set, a solvable auxiliary optimization problem (OP) is proposed to design the controller. the recursive feasibility of the auxiliary OP and the input-to-state stability of the closed-loop system are guaranteed. the validity of the developed ETMs-based anti-attack MPC algorithm is shown by an example.

关键词： Uncertain systems Predictive models Prediction algorithms Stability analysis Data models Numerical models Closed loop systems

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Design of Switched Reluctance Motor(SRM) Servo control for Robot Joints

Design of Switched Reluctance Motor(SRM) Servo Control for R...

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international conference on Electronics Technology (ICET)

作者： Yongsheng Wang Yuehong Dai Junyao Wang School of Aeronautics and Astronautics University of Electronic Science and Technology of China UESTC Chengdu China

To explore the applicability of the Switched Reluctance Motor(SRM) used in robot joints as a servo motor, a SRM servo control system was designed based on MATLAB. In this paper, MotorSolve was used to obtain the simulation data of the discrete operation of the motor, and the cerebellar model articulation controller(CMAC) was designed to learn the inductance-position angle-current and torque-position angle-current nonlinear models, the accuracy of the model is higher than that of ordinary look-up tables. the position control of the SRM servo system is realized by using cascade PID. the result shows that the servo system has a fast response time of 0. 35s under constant load, an overshoot of 5%, and an output torque fluctuation of 5.4%., which basically meets the requirements of robot joint servo control. Simultaneously, the system provides a simulation experiment platform for the follow-up research on SRM servo control for robot joints, and more advanced servo control algorithms can be studied on this basis.

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A Review on control and Economic Dispatch Methods for Microgrids

A Review on Control and Economic Dispatch Methods for Microg...

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Energy, Electrical and Power engineering (CEEPE), international conference on

作者： Weijun Lin Qingbin Wang Jingwei Long Zizhuo Lian Haoxian Liang Zhilin Liang Yunfu Power Supply Bureau China Southern Power Grid Co. Ltd Yunfu China

With the increasing penetration of renewable energy generation, MGs based on renewable energy generation have received wide attention, and the research on MGs is mainly focused on economic dispatch. At the same time, the development trend of scale and complexity of power grid makes the problem of safety and economic operation of power grid prominent, and the fault diagnosis and early warning technology of power system including MG cannot be ignored. Starting from the economic dispatch of MG, the article analyzes the research of centralized dispatch and distributed dispatch now and summarizes their characteristics in application. In addition, this paper summarizes the power grid fault diagnosis and early warning technology, and analyzes the application status of various algorithms in the field of power grid safe operation.

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Reinforcement Learning Scheduling Research for Edge Servers

Reinforcement Learning Scheduling Research for Edge Servers

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international conference on Computer Network, Electronic and Automation (ICCNEA)

作者： Yonggui Han Zhongsheng Wang School of Computer Science and Engineering Xi’an Technological University Xi’an China State and Provincial Joint Engineering Lab. of Advanced Network Monitoring and Control Xi'an Technological University Xi'an China

the rapid development of the Internet of things and big data has brought about massive amounts of data and the need for real-time responses, which traditional computing models can no longer meet. Edge computing comes into being, which pushes computing resources and services closer to the source of data generation so that data can be processed and analyzed closer to the user. the scheduling of siting strategies for edge servers is crucial for improving the performance of edge computing networks. Traditional scheduling methods for siting strategies are often based on rules or optimization algorithms, which lack adaptive and intelligent management of the network *** paper proposes a reinforcement learning DQN-based edge server siting policy scheduling method, which aims to achieve intelligent management and resource optimization of edge computing networks by learning the optimal policy. Experimental results show that the method has significant performance advantages in terms of delay, load balancing and energy consumption. the experiment adopts DQN algorithm, which is based on Q-learning and guides the agent to make decisions by optimizing Q-value function. In this paper, the reinforcement learning scheduling algorithm of edge server is studied and compared with other three algorithms. According to the experimental results, the proposed reinforcement learning scheduling algorithm reduces the delay by 7%, the energy consumption by 3%, and the load balancing by 20% compared with the other three algorithms. this shows that the algorithm has significant advantages in improving system performance.

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Effective control of Unmanned Aerial Vehicles Based on Reward Shaping

Effective Control of Unmanned Aerial Vehicles Based on Rewar...

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Robotics, control and Automation engineering (RCAE), international conference on

作者： Shengqi Kong Minne Li Yuan Zhou Zhiyuan Wang College of Computer Science and Technology National University of Defense Technology Changsha China Intelligent Game and Decision Lab IGDL Beijing China

the autonomous control of unmanned aerial vehicles (UAVs) presents a challenging problem in the field of control. Conventional autopilot designs utilize single-input, single-output (SISO) controllers, such as PID controllers, which may become unstable under certain conditions. To overcome these limitations, researchers have explored the use of reinforcement learning (RL) algorithms in UAV control. this paper reviews related works in the field and proposes a study to evaluate the impact of shaping rewards based on aircraft attitude on the effectiveness of UAV control. We investigated the application of reinforcement learning in UAV control, specifically focusing on the impact of shaping rewards based on aircraft attitude in variable wind speed environments. Two experiments were conducted to investigate the training rate and control effectiveness of agents with shaping rewards and non-shaping rewards. the findings indicate that shaping rewards based on flight attitude effectively reduce turbulence in the aircraft's flight process and outperform non-shaping rewards in altitude and heading control in the Gaussian wind speed model.

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Phenomenological Modeling and End-Point Trajectory Tracking control of a Flexible Beam with Pneumatic Soft Actuators

Phenomenological Modeling and End-Point Trajectory Tracking ...

引用

IEEE international conference of Intelligent Robotic and control engineering (IRCE)

作者： Xuefeng Sun Qingxin Meng Jundong Wu Mingliang Zhu School of Automation China University of Geosciences Wuhan Hubei China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan Hubei China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan Hubei China

As the basic construction of flexible mechanical systems, the flexible beam and its control problem have attracted widespread attention in recent years. this paper takes a flexible beam with pneumatic soft actuators (FBPSA) as the research object and studies its phenomenological modeling and end-point trajectory tracking control strategy. Firstly, we develop an experimental platform for the FBPSA and perform tests on it, gathering its input and output data. Using these collected data, we analyzed the motion characteristics of the FBPSA. Subsequently, a phenomenological model is established to describe the motion characteristics of the system, and the parameters of this model are identified through a large amount of the collected experimental data. then, a combined feedforward-feedback control strategy is proposed to achieve the end-point trajectory tracking control of the system. Finally, three sets of experiments are carried out to verify the accuracy of the established model and the effectiveness and superiority of the control strategy.

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Towards Human-Like Robotic Grasping for Industrial Applications Using Computer Vision 1

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6th international conference on Intelligent Sustainable Systems, ICISS 2023

作者： Prasada Rao Borra, Surya Sandiri, Rajendar Nalajala, Paparao Majji, Sankararao Saravanakumar, C. Chandra, K. Ramesh PVP Siddhartha Institute of Technology Vijayawada India Department of ECE Vardhaman College of Engineering Hyderabad India Department of ECE Institute of Aeronautical Engineering Hyderabad India Department of ECE GRIET Hyderabad India Department of ECE SRM Valliammai Engineering College Chennai India Department of Electronics and Communication Engineering Vishnu Institute of Technology Andhra Pradesh Kovvada India

ISBN: (数字)9789819917266

ISBN: (纸本)9789819917259

the manufacturing industries are seeing an ever-increasing need for robotic process automation. At the moment, robotic systems can only function in extremely chaotic settings. Manufacturers employ robots to assemble goods including automobiles, candy bars and technological devices. As technology has advanced, robots have found applications in a variety of fields, including medical, military strategy, underwater object discovery and planetary exploration. People who have lost limbs have benefited from robotic technology. Robots can do a lot of useful things for humans. the controller directs the position of the manipulator, while actua-tors in the joints provide the necessary motion for the robot. therefore, the controller must provide a precise value for joint variables representing the end effector’s posi-tion. An industrial robot’s manipulator has more than one way to get to its desired job or end effector position, allowing for a more precise solution to the joint vari-ables. Fault tolerance and fault deduction over a wide range are two applications of this study’s inverse kinematics-based methodology. To facilitate communication between the system and the ABB robot, a unique approach based on the file transfer protocol (FTP) has been devised. this work has shown it can be simply and safely integrated into a number of robot manipulator systems through the integration of the proposed predictive visual servoing strategies with the robot manipulator for real-world applications. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Model predictive control

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Satellite Attitude control for Emergency Mode Using Reaction Wheels and Magnetic Torquers

Satellite Attitude Control for Emergency Mode Using Reaction...

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Robotics, control and Automation engineering (RCAE), international conference on

作者： Yikang He Sen Yang Shuyu Lin Wen He Zhen Yang Key Laboratory of Advanced Manufacturing Technology of Zhejiang Province Zhejiang University Hangzhou China School of Astronautics Harbin Institute of Technology Harbin China Shanghai Institute of Spaceflight Control Technology Shanghai China

To recover the satellite operations in emergency conditions, a control design scheme for emergency mode that utilizes reaction wheels and magnetic torques is presented in this paper. Firstly, based on a highly reliable sensor suite comprising sun sensors and magnetometers, a suitable attitude control law is designed to complete the satellite attitude missions of rate damping and sun-pointing. then, considering that there are only two workable reaction wheels due to one reaction wheel failures, a control allocation law is designed to determine the control torque provided by two reaction wheels and the magnetic moment provided by magnetic torquers. Finally, the proposed method is compared with the purely magnetic control method by numerical simulations. the results indicate that the proposed method can achieve the attitude control missions after the satellite enters emergency mode, and performs better in terms of convergence and accuracy.

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Research on Task Scheduling algorithms for Cloud-Edge Collaboration 19th

Research on Task Scheduling Algorithms for Cloud-Edge Collab...

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19th EAI international conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness, QShine 2023

作者： Lu, Shuai Zhou, Haibo Zhao, Shuaishuai Xu, Wangbei Fang, Kai Tianjin300384 China Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China College of Mathematics and Computer Sciences Zhejiang A&F University Hangzhou311300 China

ISBN: (纸本)9783031651229

With the advent of the 5G era, the development of IoT technology has been accelerated. Due to the continuous increase in the amount of data waiting to be processed from the edge, edge nodes may struggle to handle such a vast amount of data. therefore, the technology of cloud-edge collaboration has emerged, and how to achieve cloud-edge collaborative task scheduling has become a current research hotspot. this article provides a detailed exposition of the relevant work on task scheduling in the cloud-edge environment, and outlines the common optimization objectives in the cloud-edge collaboration scenario. the methods used to solve task scheduling problems are classified and summarized, including heuristic, heuristic algorithm based on linear programming, and meta-heuristic algorithms. the advantages and disadvantages of each algorithm are analyzed. Finally, the development trends of large-scale task scheduling in the cloud-edge environment are discussed, providing valuable insights for achieving real-time performance, efficiency, and energy conservation in the Internet of things. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications engineering 2024.

关键词： Scheduling algorithms

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Adaptive Hybrid Neural Network Sliding Mode control of Ultrasonic Motors

Adaptive Hybrid Neural Network Sliding Mode Control of Ultra...

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IEEE international conference of Intelligent Robotic and control engineering (IRCE)

作者： Xinqiang Wang Chenyang Ding Yunlang Xu Xinyi Su Academy for Engineering and Technology Fudan University Shanghai China School of Microelectronics Fudan University Shanghai China

Nonlinear disturbances such as viscous friction, static friction and external disturbances exist in ultrasonic motors, which seriously affect their high-performance motion control process. To realize the high precision scanning motion of ultrasonic motor, an adaptive hybrid neural network sliding mode control (AHNN-SMC) method is designed. the neural network basis function part adopts a combination of Gaussian basis and partial friction model, combined with an adaptive algorithm to achieve online nonlinear compensation of the ultrasonic motor. In order to solve the problem of overestimation of switching control gain caused by the difficulty of accurate estimation of uncertain upper bound in the control process, adaptive switching gain is further adopted in this paper to cut down the influence of chatter in the control process. In order to verify the performance of AHNN-SMC in ultrasonic motor scanning motion control, position tracking simulation experiments are performed for sinusoidal signals with a maximum displacement of 20mm and compared with several algorithms. the results show that the maximum tracking error (MAE) of AHNN-SMC is 3.15 μ m and the mean error (RMSE) is 1.25 μ m, and the results indicate that the method has good position tracking performance.

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