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检索条件"任意字段=7th International Conference on Advanced Algorithms and Control Engineering, ICAACE 2024"

共 513 条记录，以下是51-60 订阅

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Quadruped Robot Motion control Method Based on Adaptive Weight Coefficients MPC 7

Quadruped Robot Motion Control Method Based on Adaptive Weig...

引用

7th international conference on advanced algorithms and control engineering, icaace 2024

作者： Nan, Zhipeng Xu, Lin Han, Chengleng Zhao, Guorui Wuhan University Of Technology Hubei Key Laboratory Of Advanced Technology For Automotive Components Wuhan China

ISBN: (纸本)9798350361445

In real-world environments, quadruped robots often need to traverse unstructured terrains and may encounter various unexpected impacts. To enhance the motion balance performance of quadruped robots when facing unknown disturbances in such environments, we propose a fuzzy adaptive weight controller based on Model Predictive control (MPC). By conducting an in-depth analysis of the impact of weight coefficients in the MPC's objective function on control effectiveness, we have designed an adaptive fuzzy algorithm. this algorithm dynamically adjusts the weight coefficients according to the current errors in the robot's roll and pitch angles, as well as their rates of change. Subsequently, the MPC controller calculates the optimal control torques using these adjusted weight coefficients. To validate the effectiveness of this strategy, we conducted simulations of lateral impacts and walking on unstructured terrains in Gazebo. the simulation results demonstrate that, under various test conditions, the proposed adaptive weight MPC controller significantly improves the robot's motion stability, showcasing its strong capability to handle unknown disturbances. © 2024 IEEE.

关键词： Model predictive control

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Kinematic Analysis and control of the Handling Robotic Arm 7

Kinematic Analysis and Control of the Handling Robotic Arm

引用

7th international conference on advanced algorithms and control engineering, icaace 2024

作者： Shi, Yu Liu, Yanchen Guo, Pengke School Of Mechanical And Electrical Engineering North University Of China Taiyuan030051 China Taiyuan Heavy Industry Co. Ltd. Technical Center Taiyuan030024 China

ISBN: (纸本)9798350361445

In terms of automated handling of heavy objects, ropes or steel cables are currently commonly used for lifting and handling. this method requires operators to constantly assist in adjusting their posture, which is not efficient and poses certain risks to operators. For this purpose, the research group has designed a six degree of freedom hydraulic robotic arm for automatic handling of a 400kg object. Firstly, the kinematic model of the robotic arm was established using the D-H parameter method. Based on the results of kinematic analysis, the workspace image of the robotic arm was drawn using Monte Carlo method. the Simulink simulation model was established, and trajectory planning simulation based on Cartesian space was conducted on the robotic arm. the simulation results were consistent with the calculation results, verifying the correctness of the kinematic model and trajectory planning algorithm of the robotic arm. Subsequently, trajectory planning experiments were conducted on the robotic arm prototype, the results showed that the robotic arm could complete the operation of the planned trajectory within 20 seconds, the automatic operation process was continuous and smooth. © 2024 IEEE.

关键词： Kinematics

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Integrated control Strategy for Nonlinear PID Cross-Coupling Contour Error Compensation Based on Active Disturbance Rejection control 7

Integrated Control Strategy for Nonlinear PID Cross-Coupling...

引用

7th international conference on advanced algorithms and control engineering, icaace 2024

作者： Lu, Yongliang Zhao, Jun School Of Mechanical Engineering Shandong University Jinan China

ISBN: (纸本)9798350361445

Improving the contour control accuracy of multi-axis servo system is one of the most significant applications of modern CNC machining. At present, the cross-coupling control (CCC) and proportional integral differential (PID) control are the most popular method to reduce contour error for multi-axis contour following tasks. Since the traditional CCC method has poor contour tracking accuracy for free-curve trajectory, and the traditional PID control system has poor interference immunity and robustness, a novel integrated control strategy of cross-coupling contour error compensation based on active disturbance rejection control, which consists of a free-curve contour error real-time estimation model, a NURBS interpolator, a novel non-linear PID (NLPID) position servo controller for position loop feedback control and contour error compensation (TNP-ADRC) and a variable gain cross-coupling controller based on non-linear PID control, is proposed. Several simulations are carried out in Matlab/Simulink environment. Firstly, the tracking performance of the proposed TNP-ADRC is simulated by the square wave signal, and then the non-uniform rational B-spline (NURBS) curve is used to simulate the contour accuracy. the simulation results indicate that compared with the commonly used integrated control strategy of cross-coupling contour error compensation which consists of CCC method and PID method, the proposed integrated control strategy can not only effectively improve the robustness and anti-interference ability of the system, but also significantly improve the contour control accuracy of the biaxial motion control system. © 2024 IEEE.

关键词： controllers

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Short-Term Wind Power Prediction under Cold Wave Weather Conditions based on Neural Prophet 7

Short-Term Wind Power Prediction under Cold Wave Weather Con...

引用

7th international conference on advanced algorithms and control engineering, icaace 2024

作者： Hu, Jiaqiu Meng, Wenchuan Tang, Jian Zhuo, Yixin Rao, Zhi Sun, Siyang Dispatching Control Center Of Guangxi Power Grid Guangxi Nanning530013 China Energy Development Research Institute China Southern Power Grid Guangdong Guangzhou510663 China

ISBN: (纸本)9798350361445

In response to the challenges faced by the power grid in Guangxi, China during the peak winter demand exacerbated by the impact of cold wave weather, this study proposes a method for short-term wind power prediction under cold wave conditions. Firstly, the TimeGAN model is employed to augment the limited dataset under cold wave climates, enhancing the adaptability of the model to such weather conditions. Secondly, the cold wave weather is categorized into three scenarios: strong winds, low temperatures with ice covering, and intense rainfall. Neural Prophet models are then utilized separately for predicting each scenario. the proposed models are validated using wind power data from a wind farm in Guangxi, demonstrating excellent predictive performance under cold wave weather conditions. © 2024 IEEE.

关键词： Wind power

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Specific Emitter Identification Based on ACGAN and STFT 7

Specific Emitter Identification Based on ACGAN and STFT

引用

7th international conference on advanced algorithms and control engineering, icaace 2024

作者： Wang, Bin Xie, Jun Wang, Feng The 38th Research Institute Of China Electronics Technology Group Corporation China Key Laboratory Of Aperture Array And Space Application China Key Laboratory Of Intelligent Information Processing Anhui Hefei230088 China School Of Computer And Information Hefei University Of Technology Hefei230601 China

ISBN: (纸本)9798350361445

Deep learning methodologies are gaining popularity for enhancing the efficiency of Specific Emitter Identification (SEI). Nevertheless, the lack of labeled datasets continues to pose a challenge in most non-cooperative scenarios for SEI. Addressing this challenge, a framework for SEI is proposed, leveraging Short-Time Fourier Transform (STFT) in conjunction with auxiliary classifier GAN(ACGAN). the Short-Time Fourier Transform of emitters is utilized as radio-frequency fingerprint for the emitters. the input latent layer is infused with label information to steer the training process of the Generative Adversarial Network. through semi-supervised training, shared weight updates are implemented for the classification network. Experimental results demonstrate that our model can achieve superior or competitive performances in several datasets compared with the former models. © 2024 IEEE.

关键词： Deep learning

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Limit Protection control for Solid Ducted Rocket Based on Command Governors 7

Limit Protection Control for Solid Ducted Rocket Based on Co...

引用

7th international conference on advanced algorithms and control engineering, icaace 2024

作者： Zhang, Zongyu Wang, Zongqing Tang, Meng Zeng, Qinghua School Of Aeronautics And Astronautics Sun Yat-Sen University Shenzhen China Hongyang Electromechanical Company Hubei SanJiang Aerospace Group Xiaogan China

ISBN: (纸本)9798350361445

Solid ducted rockets (SDRs) have long been considered the preferred power source for aircraft due to their long range, high specific impulse, and simple structure. However, their operation is constrained by various factors, including overshoot, anti-regulation, and intake unstart. To balance the trade-off between high-performance regulation and limit protection control of SDR, this paper investigates a control strategy for gas flow in SDR based on command governors (CG). A supplementary control scheme using CG is designed to ensure that the engine response does not exceed the constraint limit. the constructed command governor takes the form of a pre-filter, with the key being the construction of the maximal output admissible set (MOAS) that satisfies the limiting constraints and the utilization of the rolling optimized solvable instructions obtained from the engine model in the MOAS. the simulation results demonstrate the effectiveness of the proposed algorithm in preventing constraint violations and ensuring engine performance, indicating promising prospects for engineering applications. © 2024 IEEE.

关键词： Flow of gases

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Improved YOLOv7-Tiny for Hazardous Vehicle Detection 7

Improved YOLOv7-Tiny for Hazardous Vehicle Detection

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7th international conference on advanced algorithms and control engineering, icaace 2024

作者： Tian, Yu Zhao, Dequn Zhang, Suming Ma, Hongwei Beijing University Of Technology Faculty Of Information Technology Beijing China Beijing Aerospace System Engineering Research Institute Beijing China

ISBN: (纸本)9798350361445

In addressing the challenge of distinguishing between regular trucks and hazardous transport vehicles within the park, this paper introduces an enhanced algorithm for hazardous material vehicle detection, leveraging the YOLOv7-tiny model. the algorithm's objective is to swiftly recognize hazardous material markings on vehicles and differentiate hazardous material transport vehicles. Initially, a dataset comprising 8,000 images and 10,000 hazardous material vehicle samples is compiled. Leveraging prior knowledge of hazardous material markings enhances the detection accuracy of hazardous vehicles. Subsequently, the YOLOv7-tiny network undergoes several enhancements: the CoT-ELAN network structure is proposed to improve feature extraction for small targets by integrating attention mechanisms, and a decoupled head structure is introduced to address different aspects of classification and localization, thereby boosting overall performance. Experimental findings showcase the superior performance of the enhanced algorithm on the internally constructed dataset, achieving a 5.6% increase in average precision compared to the traditional YOLOv7-tiny model. With a detection speed of 70.5 FPS on GPU devices, the algorithm effectively meets the hazardous material vehicle detection needs within the park. © 2024 IEEE.

关键词： Hazards

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A Smoke Flow control Method for Aircraft Cargo Cabins Considering Delay and Disturbance 7

A Smoke Flow Control Method for Aircraft Cargo Cabins Consid...

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7th international conference on advanced algorithms and control engineering, icaace 2024

作者： Yang, Jianzhong Guo, Shanghua Chen, Xiyuan College Of Safety Science And Engineering Civil Aviation University Of China Tianjin China College Of Electronic Information And Automation Civil Aviation University Of China Tianjin China

ISBN: (纸本)9798350361445

In the airworthiness verification experiment of the aircraft cargo compartment fire smoke detection system, it is necessary to control the simulated smoke flow field generated by the smoke generator, in order to achieve equivalence with real fire smoke. the difficulty of simulated smoke control lies in the hysteresis effect during smoke diffusion and the nonlinearity caused by its own turbulent *** the data generated by CFD (Computational Fluid Dynamics) numerical simulation for system identification, the simulated smoke flow field is approximated as a transfer function with a delay link, and the random pulsation during the smoke turbulent diffusion process is treated as a disturbance in the model. Analyzing the influence of delay and disturbance on closed loop control of systems, And then, design a control law based on this. For the delay link, a Smith compensator is used to compensate, A sliding mode control method is used to overcome the disturbance caused by turbulence in the system, compare the control performance with PID (Proportional-Integral-Differential) algorithm. the simulation results show that the Smith compensator can effectively reduce the impact of system delay, and the sliding mode controller exhibits a strong control effect on disturbances. the combination of Smith compensator and sliding mode control can better achieve closed-loop flow control of simulated smoke. At the same time, research ideas and control methods can provide meaningful theoretical guidance for the airworthiness verification experiments of aircraft cargo fire smoke detection systems © 2024 IEEE.

关键词： Smoke

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Forest Fire Detection Method Based on Improved YOLOv7 7

Forest Fire Detection Method Based on Improved YOLOv7

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7th international conference on advanced algorithms and control engineering, icaace 2024

作者： Shi, Peiyuan Wang, Xiaopeng College Of Electronic And Information Engineering Lanzhou Jiaotong University Gansu Lanzhou China

ISBN: (纸本)9798350361445

the proposed method addresses the challenge of real-time and high-precision detection of early fires in complex forest environments, a limitation faced by existing object detection algorithms. the method is based on the improvement of YOLOv7. Firstly, the Coordinate Attention (CA) mechanism is introduced into the backbone network to capture the correlation of features at different spatial positions, enhancing the model's feature extraction capabilities. Additionally, CA is incorporated into the Feature Pyramid Network (FPN) to construct the C-FPN feature fusion network, establishing cross-level connections between shallow and deep networks to shorten the path between shallow and deep features and enhance the retrieval capability of deep network position information. Secondly, the Normalized Wasserstein Distance (NWD) is utilized instead of IoU in label assignment, Non-Maximum Suppression (NMS), and loss functions to improve regression accuracy. Finally, the network structure ELAN is improved to ELAN-P, introducing new partial convolutions to reduce floating-point calculations, redundant computations, and memory access, thereby enhancing the efficiency of the detection model. Experimental results demonstrate that compared to the YOLOv7 algorithm, the proposed method achieves a mean Average Precision (mAP) of 96.3%, a 4.6% improvement over YOLOv7. Additionally, the detection frames per second (FPS) reach 67.7 flames/s, enabling real-time and accurate detection of forest fires in complex environments. © 2024 IEEE.

关键词： Fires

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Design of Dual-Robot Collaborative Handling control System 7

Design of Dual-Robot Collaborative Handling Control System

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7th international conference on advanced algorithms and control engineering, icaace 2024

作者： Wang, Li Qian, Bingfeng Zhang, Lei Chen, Shenjie School Of Mechanics Shanghai Dianji University Shanghai China

ISBN: (纸本)9798350361445

Since single robot has great limitations in executing tasks and is difficult to meet the market demand, the dual robot control system has become a research hotspot. this paper starts from solving the problems of complex cooperative motion programming and obstacle avoidance of dual-robot. In order to solve the problems of complex programming and obstacle avoidance for cooperative movement of dual-robot, a control system for cooperative movement of dual-robot with clear logic and simple programming is designed. this paper firstly analyzes the kinematics of dual-robot and solves the inverse kinematics to accurately control the robot, then a dual-robot control system with two ABB-IRB1410 robots as the research object and PLC-300 as the upper machine is designed. the offline programming workstation of the robot is built based on Robotstudio software. the joint Angle of the carrying position of dual-robot is calculated by solving the inverse kinematics, and the collaborative carrying is programmed by using the linear motion instruction of the MoveL robot. the linear motion instruction can make the end actuator of the robot move according to the given trajectory. the end attitude of dual-robot is consistent in the process of handling, and only 6 position points are used in the program to complete the workpiece handling, and simulation and experiment are carried out. the experimental results show that the dual-robot cooperative handling control and the system operation is stable, which is beneficial to further simplify the system design of dual-robot cooperative handling. © 2024 IEEE.

关键词： control systems

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