نتایج جستجو برای: adaptive neural network observer

تعداد نتایج: 1025786  

2007
Guan-Ming Chen Wei-Yen Wang Tsu-Tian Lee C. W. Tao

In this paper, an observer-based direct adaptive fuzzy-neural controller (ODAFNC) for an anti-lock braking system (ABS) is developed under the constraint that only the system output, i.e., the wheel slip ratio, is measurable. The main control strategy is to force the wheel slip ratio to well track the optimal value, which may vary with the environment. The observer-based output feedback control...

Journal: :Complex & Intelligent Systems 2021

Abstract This paper investigates a feature tracking control method for visual servoing (VS) manipulators adaptive dynamic programming (ADP)-based the unknown dynamics. The major superiority of ADP-based optimal lies in that problem is converted to error with cost function. Moreover, an neural network observer developed approximate entire uncertainties, which are utilized construct improved By e...

Abbas Vafaei Javad Rasti Seyyed Amir Monajjemi

Reducing the number of colors in an image while preserving its quality, is of importance in many applications such as image analysis and compression. It also decreases memory and transmission bandwidth requirements. Moreover, classification of image colors is applicable in image segmentation and object detection and separation, as well as producing pseudo-color images. In this paper, the Kohene...

Journal: :international journal of advanced design and manufacturing technology 0
davoud naderi soheil ganjefar mohamad mosadeghzad

in this research optimal reconfiguration strategy of the improved srr reconfigurable mobile robot based on force-angle stability measure has been designed using genetic algorithm. path tracking nonlinear controller which keeps robot’s maximum stability has been designed and simulated in matlab. motion equations of the robot have been derived in parametric form by means of newton- euler, lagrang...

Ahmad Ghanbari Sayyed Mohammad Reza Sayyed Noorani Yasaman Vaghei,

In recent years, researches on reinforcement learning (RL) have focused on bridging the gap between adaptive optimal control and bio-inspired learning techniques. Neural network reinforcement learning (NNRL) is among the most popular algorithms in the RL framework. The advantage of using neural networks enables the RL to search for optimal policies more efficiently in several real-life applicat...

Journal: :Transactions of the Institute of Systems, Control and Information Engineers 1991

Journal: :TRANSACTIONS OF THE JAPAN SOCIETY OF MECHANICAL ENGINEERS Series A 1992

Journal: :Journal of Computer Science 2005

Journal: :Knowledge and Information Systems 2000

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