کنفرانس مهندسی برق ایران

صفحه اصلی / سی و دومین کنفرانس بین المللی مهندسی برق

Autoencoders for Input Reduction in Interval Type-2 Hyperbolic Fuzzy System Identification and Control: Experimental Results

نویسندگان :

Behnaz Mohammadi¹ Nazanin Ildarabadi² Mohammad-R Akbarzadeh-T³

1- دانشگاه فردوسی مشهد 2- دانشگاه فردوسی مشهد 3- دانشگاه فردوسی مشهد

کلمات کلیدی :

Autoencoder،Follower robotic،Interval type-2 generalized fuzzy hyperbolic systems،Uncertainty

چکیده :

One of the main challenges in real-time robot control is its computational complexity and poor performance due to environmental uncertainties and nonlinearities. Interval Type-2 Generalized Fuzzy Hyperbolic Systems (IT2-GFHS) offer a simpler inferencing process but at the cost of increased number of inputs. However, numerous inputs could lead to decreased accuracy and lower efficiency. This article presents an Interval Type-2 Generalized Fuzzy Hyperbolic Neural Network System (IT2-GFHNS) that utilizes an Autoencoder neural network to reduce the number of inputs and improve the system performance. The effectiveness of the proposed method is first examined through simulations on a quadcopter and then experimentally implemented on an EMG-driven Robotic Follower, where the system identification is achieved using IT2-GFHNS. Additionally, the sliding mode is employed as a quadcopter control mechanism, and PID control is utilized for an EMG-driven robot. This method outperforms IT2-GFHS in terms of reducing tracking error, even with the increasing number of inputs.

لیست مقالات

لیست مقالات بایگانی شده

Automated Optic Disc Segmentation in Low-Quality Retinopathy of Prematurity Retinal Images

Abolfazl Karimiyan Abdar - Reza AghaeiZadeh Zoroofi - Naser Shoeibi - Sare Safi - Alireza Ramezani - Homayoun Nikkhah - Hamid Safi - Mohammad Reza Ansari Astaneh

Designing Of Type-2 Fuzzy Formation Controller For A Class Of Nonlinear Multiagent System Using JAYA Algorithm

Arvin Attar - Mohammad Ali Badamchizadeh - Sehraneh Ghaemi