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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31-40 订阅

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Adaptive Hybrid Neural Network Sliding Mode control of Ultrasonic Motors 6

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

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6th international conference on Intelligent Robotics and control engineering, IRCE 2023

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

ISBN: (纸本)9798350326338

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. © 2023 IEEE.

关键词： Adaptive algorithms

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Design of Switched Reluctance Motor(SRM) Servo control for Robot Joints 6

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

引用

6th international conference on Electronics Technology, ICET 2023

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

ISBN: (纸本)9798350337693

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. © 2023 IEEE.

关键词： Position control

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Proceedings - 2023 6th international conference on Electronics and Electrical engineering Technology, EEET 2023

Proceedings - 2023 6th International Conference on Electroni...

引用

6th international conference on Electronics and Electrical engineering Technology, EEET 2023

ISBN: (纸本)9798350395594

the proceedings contain 36 papers. the topics discussed include: effects of dimension reduction methods on boosting algorithms for better prediction accuracies on classifications of stress EEGs;SVAE-WGAN data augmentation method for partial discharge fault detection of 5G based power intelligence system;a control strategy for electric vehicles participating in frequency regulation considering user demand and battery longevity;research on face image denoising method based on adaptive bidimensional empirical mode decomposition and stochastic resonance method;research on camera calibration technology of two-dimensional displacement measurement system based on single-chip microcomputer;and a review of face recognition methods based on lightweight deep neural networks.

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Intelligent Building Indoor Temperature control Based on Deep Reinforcement Learning 6

Intelligent Building Indoor Temperature Control Based on Dee...

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6th international conference on Renewable Energy and Power engineering (REPE)

作者： Jiang, Botao Lv, Shilin Zou, Kai Gong, Yun Gao, Ersi State Grid Zhejiang Elect Power Co Ltd Hangzhou Peoples R China

ISBN: (纸本)9798350306194;9798350306187

the sustainable development and intelligent construction of building energy systems have become an inevitable trend of global energy development. the indoor temperature control has gradually played an important role in promoting energy saving and consumption reduction of buildings in the whole society. According to the physical characteristics of the wall, this paper constructs a RC network thermodynamic model of the building system. Taking the room temperature comfort and economy as the optimization goals, a deep reinforcement learning algorithm, namely, deep deterministic policy gradient (DDPG), is employed to determine the optimal heating and cooling strategies for temperature control devices under different weather conditions. By comparing the temperature variations, energy consumption, and electricity costs, it is observed that DDPG outperforms deep Q-network (DQN) significantly. Furthermore, cross-validation using the Gurobi Optimizer demonstrates that in both summer and winter seasons, where energy consumption accounts for 75% of the total, the performance of the deep reinforcement learning algorithm is equal to or even surpasses Gurobi Optimizer. Moreover, compared with the solver's performance, DDPG's total energy consumption in summer and winter is reduced by 4%. this demonstrates that deep reinforcement learning algorithms such as DDPG exhibit high generalization capability and practicality in complex system control and scheduling problems.

关键词： indoor temperature control RC network deep reinforcement learning cross-validation

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Design of cutting vibration control method based on servo system 6

Design of cutting vibration control method based on servo sy...

引用

6th international conference on advanced Electronic Materials, Computers, and Software engineering, AEMCSE 2023

作者： Wu, Xiu Zhang, Youzhi Shao, Qiang Bao, Jiawei Liu, Yu Dalian Minzu University of China Electromechanical Engineering College China

ISBN: (纸本)9781510668249

this topic is aimed at improving the effect of chatter generated in the cutting process on the machining quality of workpieces. By controlling the servo system, the influence of lathe vibration on workpiece quality is reduced, and the cutting process is studied. According to the signal of effective vibration of workpiece, the control device of tool feed is designed to control the cutting elements in the cutting process, so as to effectively improve the machining quality and efficiency. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Servomechanisms

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Fault Detection for Positive Switched Systems with All Modes Unstable 6

Fault Detection for Positive Switched Systems with All Modes...

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6th international conference on Intelligent Robotics and control engineering, IRCE 2023

作者： Su, Qingyu Fan, Zhongxin Li, Jian School of Automation Engineering Northeast Electric Power University Jilin132012 China Jilin Provincial Key Laboratory of Advanced Control Technology of Smart Energy Jilin132012 China School of Automation Southeast University Nanjing210096 China

ISBN: (纸本)9798350326338

Exponential stability, L1-gain performance and fault detection are investigated in this paper for continuous positive switched system (PSS) when there exists no stable subsystems. To eliminate the instability brought by the unstable modes ensure the exponential stbility, a time-driven switching strategy is proposed by means of the average dwell time approach. then, the L1-gain performance for the PSS is guaranteed. Additionally, the stable filter design is converted into the L1-gain analysis. Sufficient conditions are deduced to guarantee the L1-gain performance with exponential stability in terms of linear matrices inequalities (LMIs). Finally, an example is provided to test and verify the effectiveness and practicality. © 2023 IEEE.

关键词： Lyapunov functions

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A Comparative Analysis of Intelligent Algorithm-Based Tuning of PID controller for Speed control of BLDC Motor 6

A Comparative Analysis of Intelligent Algorithm-Based Tuning...

引用

6th international conference on Electrical Information and Communication Technology, EICT 2023

作者： Ahmed, Anis Bishnu, Neloy Prosad Roy, Naruttam Kumar Khulna University of Engineering & Technology Department of Electrical and Electronic Engineering Khulna9203 Bangladesh

ISBN: (纸本)9798350370836

Brushless DC (BLDC) motors have gained prominence for their superior efficiency, reliability, and extended lifespan due to the absence of brushes. PID controllers effectively regulate the speed or position of BLDC motors by adjusting the motor's input voltage based on an error signal derived from the difference between the desired and actual speed or position, ensuring precise and stable operation. In this paper, a PID controller is tuned for the speed control of the BLDC motor using Particle Swarm Optimization (PSO) and Genetic algorithm (GA). the system is developed on the MATLAB/Simulink platform, and a comparative analysis is performed between the PSO and GA-based tuning of the PID controller. the preliminary result demonstrates that the GA-PID controller outperforms the PSO-PID controller regarding faster rise time and percentage of overshoot. On the contrary, PSO-PID performs better in the case of stability and robustness with a larger negative magnitude of the real part of dominating eigenvalues. © 2023 IEEE.

关键词： Genetic algorithms

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Neural State and Disturbance Observer-based Sliding Mode control of a Unicycle Robot 6

Neural State and Disturbance Observer-based Sliding Mode Con...

引用

6th IEEE international conference on advanced Systems and Emergent Technologies, IC_ASET 2023

作者： Nawress, Barhoumi Lakhal, Asma Najet Gharbi Braiek, Naceur Benhadj Laboratory of Advanced Systems B.P. 743 Marsa2078 Tunisia National Engineering School of Carthage Tunisia

ISBN: (纸本)9798350321029

this paper presents the synthesis of a hybrid control applied to a Unicycle Mobile Robot (UMR) based on modified Sliding Mode control approach (SMC) integrated with Neural State Observer (NSO) and Nonlinear Disturbance Observer (NDO). Furthermore, Lyapunov's direct method is used to ensure the stability of the closed-loop control on the one hand, and the stability of the neural state observer based on the backpropagation algorithm on the other hand. the advantages of the presented hybrid controller for velocity and tracking the trajectory of a mobile robot are revealed by simulation results. © 2023 IEEE.

关键词： Sliding mode control

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Machine learning prediction models for AFM virtual imaging system 6

Machine learning prediction models for AFM virtual imaging s...

引用

2023 6th international conference on advanced algorithms and control engineering, icaace 2023

作者： Yang, Jinxin Xu, Hongmei Liu, Xuwei Yuan, Lixin International Research Centre for Nano Handling and Manufacturing of China Changchun University of Science and Technology Changchun130022 China Ministry of Education Key Laboratory for Cross-Scale Micro and Nano Manufacturing Changchun University of Science and Technology Changchun130022 China Centre for Opto/Bio-Nano Measurement and Manufacturing Zhongshan Institute of Changchun University of Science and Technology Zhongshan528437 China

Nowadays, virtual laboratories are widely used in education and training in universities. Such virtual labs do gain some effect in teaching, assisting students to be familiar with the experimental steps. However, these systems tend to be relatively simple. there is room for improvement in helping students understand the experimental principles. this is particularly evident in the teaching of atomic force microscopy. In order to overcome these shortcomings of the AFM virtual laboratory, we present a virtual AFM imaging system with a lower-resolution contact mode. We restore the core principle of the beam deflection method in AFM using the unity3D development platform. Several machine learning techniques are employed to build an imaging prediction model. Since no public dataset is available for the task of prediction of topographical maps, we create the first dataset of grating samples for prediction. the result indicates that the proposed topographical map prediction model with the best performance is CatBoost. We prove the feasibility of building a virtual AFM imaging system with the ability to visualize internal structures and predict sample topographical maps. this work has important applications related to the 3D dynamic display of the AFM scanning and imaging process and user experience training. At the same time, it can help users get a preliminary understanding of the imaging effect of different types of experimental samples under AFM, providing a new idea for the construction of AFM virtual laboratories. © Published under licence by IOP Publishing Ltd.

关键词： Forecasting

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the Design and Implementation of a Waypoint-Based Autonomous control System on a Low-Level controller for Self-Driving Vehicles 6

The Design and Implementation of a Waypoint-Based Autonomous...

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6th international conference on Vocational Education and Electrical engineering, ICVEE 2023

作者： Happyanto, Dedid Cahya Istiqfariandi, Dewa Pramudya Alasiry, Ali Husein Electronic Engineering Polytechnic Institute of Surabaya Electrical Engineering Department Surabaya Indonesia

ISBN: (纸本)9798350326642

Autonomous land transportation vehicles and Electric Vehicles (EV) have become the main choice of the majority of society due to their environmentally friendly nature. Furthermore, the acceleration of autonomous vehicle research can also reduce traffic accidents caused by human error, which have been significantly high in the last 10 years. However, the cost required to obtain assistance from autonomous systems still tends to be expensive. this paper presents the development of a device utilizing an advanced RISC Machine (ARM) Cortex-An advanced RISC Machine (ARM) Cortex-M4 STM32F411 microcontroller system with 32-bit architecture. this system offers optimal performance at a cost-effective price point. the proposed autonomous system is designed based on the waypoint method as a reference to the vehicle's position. the Global Navigation Satellite System (GNSS) accessed through the U-Blox NEO-M8P module provides position data, whereas the HMC5883L magnetometer provides orientation data. the position data is further processed by utilizing a Kalman filter to enhance accuracy and reduce computational burden. the error detection angle read by the E-Compass is only 0.31% with the ground speed testing in comparison with true speed from car odometry with an average error of 1%, thus supporting good data accuracy, achieved with a track error of only 0.06 meters in real-scale environmental testing. this demonstrates the successful implementation of autonomous control algorithms on the low-level controller. © 2023 IEEE.

关键词： controllers

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