نتایج جستجو برای: adaptive fuzzy control

تعداد نتایج: 1559286  

Journal: :مکانیک سازه ها و شاره ها 0
محمد مهدی فاتح استاد کنترل، دانشکده مهندسی برق و رباتیک، دانشگاه شاهرود، شاهرود مجید عابدین زاده شهری کارشناس ارشد رباتیک،دانشکده مهندسی برق، دانشگاه شاهرود، شاهرود

a mobile manipulator robot is known as a complex system due to some properties such as coupling between the manipulator and mobile chassis, holonomic and nonholonomic constraints, multivariable and nonlinear dynamics. the control of robot faces the external disturbance, parametric uncertainty and unmodeled dynamics. therefore, the use of an adaptive fuzzy system is suggested for its capability ...

Journal: :Advances in Automobile Engineering 2012

The camera stabilizer stabilizes the camera’s line of sight by isolating the camera from the model uncertainties, disturbances of operating environment and system movements. This paper presents a voltage-base optimal adaptive fuzzy sliding mode control for camera stabilizer. In this proposed control method, a voltage-base sliding mode controller is applied. But unfortunately, undesirable ...

پایان نامه :وزارت علوم، تحقیقات و فناوری - دانشگاه فردوسی مشهد - دانشکده مهندسی 1389

abstract type-ii fuzzy logic has shown its superiority over traditional fuzzy logic when dealing with uncertainty. type-ii fuzzy logic controllers are however newer and more promising approaches that have been recently applied to various fields due to their significant contribution especially when the noise (as an important instance of uncertainty) emerges. during the design of type- i fuz...

Journal: :the modares journal of electrical engineering 2015
mohammad reza soltanpour pooria otadolajam mahmoodreza soltani

in this paper, an optimal adaptive fuzzy integral sliding mode control is presented to control the robot manipulator position tracking in the presence of uncertainties and permanent magnet dc motor. in the proposed control, sliding surface of the sliding mode control is defined according to the information of position tracking error, derivatives, and error integral. in order to estimate bounds ...

Journal: :journal of ai and data mining 2015
m. vahedi m. hadad zarif a. akbarzadeh kalat

this paper presents an indirect adaptive system based on neuro-fuzzy approximators for the speed control of induction motors. the uncertainty including parametric variations, the external load disturbance and unmodeled dynamics is estimated and compensated by designing neuro-fuzzy systems. the contribution of this paper is presenting a stability analysis for neuro-fuzzy speed control of inducti...

A. Akbari, M. Baghaeian,

In this paper, the enhancement of vehicle stability and handling is investigated by control of the active geometry suspension system (AGS). This system could be changed through control of suspension mounting point’s position in the perpendicular direction to wishbone therefore the dynamic is alternative and characteristics need to change. For this purpose, suitable controller needs to change...

Journal: :iranian journal of fuzzy systems 2014
hongyun yue junmin li

in this paper, an adaptive fuzzy control scheme is proposed for a class of perturbed strict-feedback nonlinear systems with unknown discrete and distributed time-varying delays, and the proposed design method does not require a priori knowledge of the signs of the control gains.based on the backstepping technique, the adaptive fuzzy controller is constructed. the main contributions of the paper...

Journal: :journal of physical & theoretical chemistry 2015
jalal javadi moghaddam mostafa mirzaei masood madani mohammadreza norouzi atena khodarahmi

in this paper, an adaptive neuro fuzzy sliding mode based genetic algorithm (anfsga) controlsystem is proposed for a ph neutralization system. in ph reactors, determination and control of ph isa common problem concerning chemical-based industrial processes due to the non-linearity observedin the titration curve. an anfsga control system is designed to overcome the complexity of precisecontrol o...

Journal: :Journal of Korean Institute of Intelligent Systems 2003

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