نتایج جستجو برای: adaptive fuzzy pid

تعداد نتایج: 288560  

2011
BASIL HAMED AHMAD EL KHATEB

The design of controllers for nonlinear systems in industry is a complex and difficult task. One approach which has shown promise for solving nonlinear control problems is the use of fuzzy logic control. This paper proposes a new method utilizing proportional–integral-derivative (PID) control as a hybrid fuzzy PID controller for nonlinear system. The salient feature of the proposed approach is ...

2016
A. Bousbaine A. Bamgbose A. K. Joseph

This paper presents the design of a Fuzzy PID controller (FPID) based on fuzzy logic with a PID structure with many valued logic and reasoning. The self-turning Fuzzy PID control take in an error and the rate of change of error of the altitude and attitude of the quadrotor as the input to the fuzzy controller and use the fuzzy rules to adjust the PID parameter automatically. Simulations have be...

2015
Ravi Kumar Sahu Sachin Tyagi Suresh Chandra Gupta

This paper gives a framework of supervisory control of boiler drum level system. The design and implementation of this process is done by the LabVIEW software. The data of the process variables Level from the boiler system need to be logged in a database for further analysis and supervisory control. A LabVIEW based data logging and supervisory control program simulates the process and the gener...

2000
R. - J. Wai J. - D. Lee

The study mainly focuses on the development of three model-free control strategies including a simple proportional-integral-differential (PID) scheme, a fuzzy-neural-network (FNN) control and an adaptive control for the positioning of a hybrid magnetic levitation (maglev) system. In general, the lumped-parameters dynamic model of a hybrid maglev system can be derived from the energy balance. In...

2017
Vijaya Santhi

1PG student, Dept of EEE, Andhra University (A), Visakhapatnam, India 2Assistant Professor, Dept of EEE, Andhra University (A), Visakhapatnam, India ---------------------------------------------------------------------***--------------------------------------------------------------------Abstract – In this paper, a robust control system with the fuzzy sliding mode controller and sliding mode co...

ژورنال: کنترل 2020

At present, the use of unmanned aerial vehicles (UAVs) has been increased dramatically. The reasons for this development are cheapness, smallness, simplicity, and diversity of missions. The simplicity of guidance and control of multi-rotor drones is that they are equipped with an autopilot system. This system is responsible for flying control. UAVs do not have a high weight and often have three...

2012
Constantin Volosencu

After the development of fuzzy logic, an important application of it was developed in control systems and it is known as fuzzy PID controllers. They represent interest in order to be applied in practical applications instead of the linear PID controllers, in the feedback control of a variety of processes, due to their advantages imposed by the non-linear behavior. The design of fuzzy PID contro...

Journal: :ISA transactions 2014
Mohammad El-Bardini Ahmad M El-Nagar

In this paper, the interval type-2 fuzzy proportional-integral-derivative controller (IT2F-PID) is proposed for controlling an inverted pendulum on a cart system with an uncertain model. The proposed controller is designed using a new method of type-reduction that we have proposed, which is called the simplified type-reduction method. The proposed IT2F-PID controller is able to handle the effec...

2008
B. M. Mohan Arpita Sinha

This paper deals with the simplest fuzzy PID controllers which employ two fuzzy sets for each of the three input variables and four fuzzy sets for the output variable. Mathematical model for a fuzzy PID controller is derived by using asymmetric Γ-function type and L-function type membership functions for each input, asymmetric trapezoidal membership functions for output, algebraic product trian...

2010
Pornjit Pratumsuwan Siripun Thongchai Surapun Tansriwong

Problem statement: While classical PID controllers are sensitive to variations in the system parameters, Fuzzy controllers do not need precise information about the system variables in order to be effective. However, PID controllers are better able to control and minimize the steady state error of the system. To enhance the controller performance, hybridization of these two controller structure...

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