AI Article Synopsis
Article Abstract
This paper outlines a precision motion stage actuated by using a voice coil motor with a floating stator. For getting good performance, a multi-mode sliding mode control (MMSMC) was designed to operate this linear motion stage. MMSMC contains two sliding mode controllers: a sliding-mode control (SMC) and an integral sliding-mode control. The switching of two SMCs will be activated according to the setting error threshold. In order to eliminate the chattering phenomenon, a soft switching control is developed to replace the signum function with a smooth function. To obtain improved performance, a fuzzy controller and an adaptive controller are introduced into the MMSMC to form a fuzzy adaptive multi-mode sliding mode control (FAMMSMC). The fuzzy control is adopted to tune the slope of the sliding mode function, and the gain of the switching control is tuned according to the adaptive law. The results of the experiments are provided to make a comparison with the FAMMSMC, MMSMC, and proportional-integral-derivative control. The experimental results show that good positioning and tracking performance can be provided by using FAMMSMC.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1063/1.5059365 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
One-Instant Flux Observer design for Three-Phase induction motor with reduced bound active load rejection speed controller.
An Acad Bras Cienc
January 2025
University of Technology, Department of Control and System Engineering, Baghdad, 10066, Iraq.
Latency in flux observation has an adverse effect on the performance of observer-based field-oriented speed control for three-phase induction motor (IM). The reduction of the convergent rate of estimation errors could improve the performance of speed-controlled IM based on flux observers. The main contribution is to design a fast convergent flux observer, which provides bounded estimation error immediately after one instant of motor startup.
View Article and Find Full Text PDFVariable-Parameter Impedance Control of Manipulator Based on RBFNN and Gradient Descent.
Sensors (Basel)
December 2024
Xi'an Institute of Optics and Precision Mechanics of CAS, Xi'an 710119, China.
During the interaction process of a manipulator executing a grasping task, to ensure no damage to the object, accurate force and position control of the manipulator's end-effector must be concurrently implemented. To address the computationally intensive nature of current hybrid force/position control methods, a variable-parameter impedance control method for manipulators, utilizing a gradient descent method and Radial Basis Function Neural Network (RBFNN), is proposed. This method employs a position-based impedance control structure that integrates iterative learning control principles with a gradient descent method to dynamically adjust impedance parameters.
View Article and Find Full Text PDFAltered Static and Dynamic Functional Network Connectivity and Combined Machine Learning in Stroke.
Brain Topogr
January 2025
Department of Radiology, Jiangxi Provincial People's Hospital, The First Affiliated Hospital of Nanchang Medical College, No 152, Ai Guo Road, Dong Hu District, Nanchang, Jiangxi, 330006, China.
Stroke is a condition characterized by damage to the cerebral vasculature from various causes, resulting in focal or widespread brain tissue damage. Prior neuroimaging research has demonstrated that individuals with stroke present structural and functional brain abnormalities, evident through disruptions in motor, cognitive, and other vital functions. Nevertheless, there is a lack of studies on alterations in static and dynamic functional network connectivity in the brains of stroke patients.
View Article and Find Full Text PDFReorganization of Dynamic Network in Stroke Patients and Its Potential for Predicting Motor Recovery.
Neural Plast
January 2025
Department of Neurology, The Fifth Affiliated hospital of Guangxi Medical University, The First People's Hospital of Nanning, Nanning, China.
The investigation of brain functional network dynamics offers a promising approach to understanding network reorganization poststroke. This study aims to explore the dynamic network configurations associated with motor recovery in stroke patients and assess their predictive potential using multilayer network analysis. Resting-state functional magnetic resonance imaging data were collected from patients with subacute stroke within 2 weeks of onset and from matched healthy controls (HCs).
View Article and Find Full Text PDFParallel layered scheme-based integrated orbit-attitude-vibration coupled dynamics and control for large-scale spacecraft.
ISA Trans
December 2024
National Key Laboratory of Aerospace Flight Dynamics, School of Astronautics, Northwestern Polytechnical University, Xi'an 710072, China; Research & Development Institute of Northwestern Polytechnical University in Shenzhen, Shenzhen 518057, China. Electronic address:
This paper investigates an integrated model-control scheme for large-scale spacecraft, focusing on orbit-attitude-vibration dynamics subject to strong time-varying coupling characteristics. The proposed scheme aims to achieve cooperative modeling and control for orbit maintenance, attitude stabilization and vibration suppression simultaneously. An integrated dynamic model is established using the Absolute Nodal Coordinate Formulation and Lagrangian mechanics, where time-varying coupling terms are preserved to enhance model integrity, contrasting with the reduction and decoupling methods commonly adopted in existing literature.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!