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A Neural PID End-effector controller for Robotic Manipulator with Joint Position Constraints

A Neural PID End-effector Controller for Robotic Manipulator...

引用

2023 international conference on System science and engineering, ICSSE 2023

作者： Nguyet, Nguyen Tran Minh Ba, Dang Xuan Faculty of Electrical and Electronics Engineering Ho Chi Minh City Viet Nam Department of Automatic Control Ho Chi Minh City Viet Nam

ISBN: (纸本)9798350322941

We present a novel efficient method to control the end- effector of robotic manipulators without solving the inverse kinematics problem in the presence of the hard bound on the joint space motion. The basic Proportional-Integral-Derivative (PID) controller is combined with a nonlinear law to track the position and control the joint move within physical limits. To provide the adaptive ability of such the controller, a neural control signal is integrated to compensate for the internal and external disturbances in the robot dynamic. Stability of the closed-loop system is guaranteed by Lyapunov constraints. The proposed controller is validated in intensive simulation results. © 2023 IEEE.

关键词： End effectors

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automatic Power Supply Availability Indicator through SMS 3

Automatic Power Supply Availability Indicator through SMS

引用

3rd international conference on Ubiquitous computing and Intelligent Information Systems, ICUIS 2023

作者： Logeswaran, T. Gopi, M. Manoj Kumar, M. Manooj, P. Navaneethan, G. Surendar, V. Kongu Engineering College Department of Electrical and Electronics Engineering Perundurai India Kongu Engineering College Department of Electrical and Electronics Engineering Perundurai638 052 India

ISBN: (纸本)9798350306989

Power supply availability plays a crucial role in the operations, product quality, and customer satisfaction of an ice cream company. Any power outages can disrupt the production process, leading to delays and potential losses. To mitigate these risks, it is essential for the company to have a power supply availability indicator. This indicator allows them to promptly identify power interruptions and take necessary measures to minimize production downtime. Continuous refrigeration is vital for maintaining the quality and preventing spoilage of ice cream. By having an indication of power supply availability, the company can ensure that their refrigeration systems are functioning properly. In the event of a power outage, they can take immediate action to mitigate the impact on their perishable inventory. Power fluctuations or outages can also affect the quality and consistency of ice cream production. Monitoring power supply availability enables the company to identify any issues related to power stability and make necessary adjustments to maintain the desired quality standards. Furthermore, sudden power surges or an unstable power supply can damage sensitive equipment such as ice cream machines, freezers, or electronic control systems. With a power supply availability indicator in place, the ice cream company can implement measures to safeguard their equipment, such as using surge protectors or backup power solutions. Consistent power supply is essential for uninterrupted service to customers. By promptly addressing power supply issues, the company can minimize disruptions in their operations, meet customer demands, and maintain their reputation for reliability and customer satisfaction. To achieve this, integrating a GSM module and Arduino can provide real-time notifications to relevant personnel within the ice cream company. These notifications enable quick responses to power interruptions, implementation of backup measures if necessary, and keeping stakeholders in

关键词： Quality control

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ANN based Harmonic Extraction in DFIG Fed DSTATCOM System 7

ANN based Harmonic Extraction in DFIG Fed DSTATCOM System

引用

7th international conference on Circuit Power and computing Technologies, ICCPCT 2024

作者： Vijayasarathi, N. Senthilkumar, Masan Ragul, S. Pandi, P. Vasanthprakash, M. Karthikeyan, D. Chettinad College of Engineering and Technology Department of Electrical and Electronics Engineering Tamil Nadu Karur India SRM Institute of Science and Technology Department of Electrical and Electronics Engineering Chennai India

ISBN: (纸本)9798350372816

The evolution of the renewable energy is the best solution for environment to reduce the pollution. Due to the fastest development of the Wind power penetration in the power system many countries offer the stable operations of power system. The most widely installed machine in the wind farm is Doubly Fed Induction Generator (DFIG).The operation of a wind energy conversion system (WECS) is based on a DFIG which is Sensitive to unbalanced non-linear load. In the proposed system the AC source is given to the non-linear load, to reduce the fluctuation the control function Distribution Static Synchronous Compensator (DSTATCOM) is used where the Input power is fed to the DFIG, it converts the AC voltage to DC and fed to Voltage Source Invertor (VSI). The reference and actual current get combined and passes to the Proportional Integral (PI) controller which is used to adjust reference and actual values and then fed to the Pulse Width Modulation (PWM) generator. The source voltage and source current are given to the DQ theory which produce the reference current and then fed to Artificial Neural Network (ANN) classifier which is used to reduce the harmonics. The PWM generator which improve the power quality and generate pulses which is applied to VSI and thereby, the generation of an opposing current is injected to the Point of Common Coupling (PCC). The design process is accessed by the MATLAB simulation. © 2024 IEEE.

关键词： MATLAB

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Neural Contextual Adaptation (NCA): For Unsupervised Learning in Dynamic Environments 3

Neural Contextual Adaptation (NCA): For Unsupervised Learnin...

引用

3rd international conference on Intelligent and Innovative Technologies in computing, electrical and Electronics, IITCEE 2025

作者： Praveen Kumar, G.D. Sanjan, S. Suraj, P. Rohan, U.A. Srinivas, R. Thanush, V. Visvesvaraya Technological University P.E.S College of Engineering Department of Computer Science and Engineering Mandya India

ISBN: (数字)9798331515911

ISBN: (纸本)9798331515911

In recent years, artificial intelligence (AI) has made significant strides in various domains, primarily driven by supervised learning techniques requiring vast amounts of labeled data. However, real-world applications, particularly those involving rapidly changing environments, demand models capable of autonomous adaptation without the need for extensive labeled datasets. In this paper, we present a novel framework for unsupervised learning that allows AI models to dynamically adapt in real-time to changing environments. Our approach leverages a combination of self-organizing maps and contrastive predictive coding to enhance model flexibility and adaptability across diverse settings. We introduce an architecture that incorporates temporal data processing and on-the-fly adaptation mechanisms, enabling the model to learn and generalize from evolving data distributions. Through extensive practical assessments and experimentation, we demonstrate our model's ability to outperform existing unsupervised approaches in real-time object detection and decision-making scenarios. The results, which show a significant reduction in model retraining time and increased adaptability to novel environments, suggest that our framework can be applied to various fields including robotics, autonomous vehicles, and dynamic control systems. © 2025 IEEE.

关键词： Self-supervised learning

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Two-stage Active Disturbance Rejection control in aerospace applications: The case of an orbit transfer for a point mass satellite.

Two-stage Active Disturbance Rejection Control in aerospace ...

引用

international conference on electrical engineering, computing science and automatic control (CCE)

作者： Mario Andrés Aguilar-Orduña Hebertt José Sira-Ramírez Brian Camilo Gómez-León Rubén Alejandro Garrido-Moctezuma Electrical Engineering Department Cinvestav-IPN Mexico City Mexico Automatic Control Department Cinvestav-IPN Mexico City Mexico

Technological advances have led to the development of smaller and more efficient satellites, which have gained popularity in various fields including education, research, and communications. However, disturbances such as gravitational forces, atmospheric drag, and space debris may affect their orbits. This article proposes a two-stage Active Disturbance Rejection control (ADRC) approach for the orbit transfer of small satellites. The paper presents the control design procedure and showcases numerical simulations, demonstrating the technique’s effectiveness in the particular case of study.

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controlling Network-Coupled Neural Dynamics with Nonlinear Network control Theory 8th

Controlling Network-Coupled Neural Dynamics with Nonlinear N...

引用

8th international conference on computing, control and Industrial engineering, CCIE 2024

作者： Xia, Zhongye Li, Weibin Liang, Zhichao Lou, Kexin Liu, Quanying Southern University of Science and Technology Shenzhen China

ISBN: (纸本)9789819769339

electrical stimulation has been an emerging technique for treating neural disorders. However, the previous studies mainly used empirical methods to select stimulation parameters and linear optimal control theory-based methods to obtain optimal control strategies. This paper offers a feasible solution to the problem of controlling the temporal dynamics of complex nonlinear network-coupled dynamical systems, specifically in terms of neural dynamics. For systems that meet two simple conditions, i.e., Lipschitz continuity and quadratic condition, we derive a control strategy with theoretical guarantees of controllability based on the Lyapunov direct method. To verify the performance of the derived control strategy, we perform numerical experiments on two nonlinear network-coupled dynamical systems that emulate phase synchronization and neural population dynamics. The results of the numerical experiments demonstrate the feasibility and effectiveness of our control strategy when applied to systems that closely resemble real-world systems, which provides robust theoretical and practical insights for future applications. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： controllability

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Path Planning for Platform AMR Loading Based on Particle Swarm Optimization 6

Path Planning for Platform AMR Loading Based on Particle Swa...

引用

6th international conference on Robotics, Intelligent control and Artificial Intelligence, RICAI 2024

作者： Lv, Ming Lan, Ting Huang, Ming Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo China

ISBN: (纸本)9798331541699

In modern warehouse automation, the platform environment to the automatic loading of goods in the container is basically through manual or large conveyor belt machinery to complete, the container is dark and narrow, easy to due to the goods scuffing or the target point is not clear resulting in reduced efficiency. The automatic loading of mobile robots can solve these problems, but at present there are fewer autonomous mobile robot solutions applied to the platform container environment. In this paper, A path planning algorithm is proposed for platform loading tasks, in which LiDAR scans the container to calculate the coordinates of the loading positions and obtains the best third-order Bezier curve based on particle swarm optimization. The experiment proves that the algorithm can effectively get the loading points in the container and fit an excellent smooth route to improve the efficiency of navigation. © 2024 IEEE.

关键词： Particle swarm optimization (PSO)

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Identification of Lung Lesions in Computed Tomography Scan Images using Machine Learning Techniques 14

Identification of Lung Lesions in Computed Tomography Scan I...

引用

14th IEEE international conference on control System, computing and engineering, ICCSCE 2024

作者： Abdullah, Mohd Firdaus Sulaiman, Siti Noraini Binti Osman, Muhammad Khusairi Karim, Noor Khairiah A. Ani, Adi Izhar Che Ahmad, Nurfadzilah Universiti Teknologi MARA Cawangan Pulau Pinang Centre for Electrical Engineering Studies Permatang Pauh Pulau Pinang13500 Malaysia Advanced Medical & Dental Institute Universiti Sains Malaysia Bertam Regenerative Medicine Cluster Kepala Batas Pulau Pinang13200 Malaysia Universiti Teknologi MARA Centre for Electrical Engineering Studies Selangor Shah Alam40450 Malaysia

ISBN: (纸本)9798350364507

Lung cancer is a common cause of death among people throughout the world. Other methods for detecting lung cancer include computed tomography (CT), magnetic resonance imaging (MRI), and radiography. This method suggests CT is useful for detecting lung cancer since it is widely available, has a shorter imaging time, and is less expensive. For clinical analysis and effective preventive planning by medical authorities to lower the number of fatalities, early diagnosis of lung lesions is crucial. Visual score is a typical method used by skilled radiologists to manually identify lesions on CT images. Nevertheless, the manual approach is labor-intensive, time-consuming, tedious, and visible. This research proposes a method for automatically detecting soft lung tissue lesions for CT images. To detect lung lesions from CT scans, the system employs image processing and machine learning techniques. The proposed automatic identification system divided into three stages. The first stage is image acquisition and data collection. The second stage proposed method involved designing a procedure for lung region segmentation using an image processing technique specifically for lung region for detection of lesions. The final stage explains an automated lesion identification for further classifying the lesion and non-lesion from CT scan lung images based on geometrical properties that have been calculated. Finally, a system that utilized the best of above-mentioned methods is proposed to perform the automated lesion detection. The method achieved high capability for automatically identifying lung lesions near the manually delineated lesion by radiologists with 98% accuracy. These findings show the possible used of this approach as an assisted tool for the radiologist in detecting lung lesions. © 2024 IEEE.

关键词： Lung cancer

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FPGA Simulation for computing Pseudoinverse Matrices

FPGA Simulation for Computing Pseudoinverse Matrices

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international conference on electrical engineering, computing science and automatic control (CCE)

作者： Gerardo Marcos Tornez Xavier Luis Martín Flores Nava Felipe Gómez Castañeda José Antonio Moreno Cadenas UPIEM-IPN Energy and Electronics Academic Mexico City Mexico Electrical Engineering Department CINVESTAV-IPN Mexico City Mexico

Many scientific and engineering processing models of big data deal with classification tasks. In particular, current intelligent approaches work efficiently for them, as they use neural techniques with shallow architectures. The Extreme Learning Machine (ELM), which is a one-hidden layer feedforward neural network, is capable of achieving high accuracy in these tasks. Moreover, one of its weighting matrices is the pseudoinverse of the hidden data. In this sense, this work presents meaningful results of computing the Moore-Penrose pseudoinverse for the ELM, using a recurrent model. The numerical simulations were based on an FPGA framework used to design a pseudoinverse-computing core.

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Research on Energy-efficient Speed control for automatic Train Operation Based on Dueling-DQN Algorithm 6

Research on Energy-efficient Speed Control for Automatic Tra...

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6th international conference on Computer Information science and Application Technology, CISAT 2023

作者： Lu, Tian Liu, Bohong Shi, Yi School of Automation and Electrical Engineering Lanzhou Jiaotong University Gansu Lanzhou730070 China

ISBN: (纸本)9781510668546

In order to realize a better train autopilot energy-saving operation control strategy, a train autopilot method based on Dueling-DQN algorithm is proposed with the train as the research object. Firstly, the train control model is established by considering the train operation demand comprehensively. Secondly, the idea of dueling network is introduced to change the structure of DQN network and prevent the problem of overestimation of value function. Finally, experimental simulations are conducted to compare with the DQN method and explore the feasibility of the method. The experiments are carried out to verify the train operation strategy method by simulating the actual line conditions. From the experimental results, it can be seen that the train operation meets the actual requirements. The energy consumption is 25.4% more energy-efficient than the actual operation, and the convergence speed of the algorithm is improved by about 40% compared with DQN. The Dueling-DQN method can improve the efficiency of the algorithm and can form an energy-efficient operation strategy that is better than the speed control in actual operation under the condition of satisfying the automatic train driving performance, which is meaningful for improving the intelligence of automatic train operation. © 2023 SPIE.

关键词： Speed control

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