scholarly journals Improved Transient Performance of a Fuzzy Modified Model Reference Adaptive Controller for an Interacting Coupled Tank System Using Real-Coded Genetic Algorithm

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Asan Mohideen Khansadurai ◽  
Valarmathi Krishnasamy ◽  
Radhakrishnan Thota Karunakaran
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy Logic Controller ◽  
Adaptive Controller ◽  
Transient Performance ◽  
Model Reference ◽  
Modified Model ◽  
Real Coded Genetic Algorithm ◽  
Tank System ◽  
Model Reference Adaptive ◽  
The Membership Function

The main objective of the paper is to design a model reference adaptive controller (MRAC) with improved transient performance. A modification to the standard direct MRAC called fuzzy modified MRAC (FMRAC) is used in the paper. The FMRAC uses a proportional control based Mamdani-type fuzzy logic controller (MFLC) to improve the transient performance of a direct MRAC. The paper proposes the application of real-coded genetic algorithm (RGA) to tune the membership function parameters of the proposed FMRAC offline so that the transient performance of the FMRAC is improved further. In this study, a GA based modified MRAC (GAMMRAC), an FMRAC, and a GA based FMRAC (GAFMRAC) are designed for a coupled tank setup in a hybrid tank process and their transient performances are compared. The results show that the proposed GAFMRAC gives a better transient performance than the GAMMRAC or the FMRAC. It is concluded that the proposed controller can be used to obtain very good transient performance for the control of nonlinear processes.

scholarly journals Experimental simplified rule of self tuning fuzzy logic-model reference adaptive speed controller for induction motor drive

2020 ◽  
Vol 20 (3) ◽  
pp. 1653
Author(s):  
M.Z. Ismail ◽  
M.H.N. Talib ◽  
Z. Ibrahim ◽  
J. Mat Lazi ◽  
Z. Rasin
Keyword(s):  
Fuzzy Logic ◽  
Induction Motor ◽  
Fuzzy Logic Controller ◽  
Adaptive Controller ◽  
Tuning Parameter ◽  
Model Reference ◽  
Wide Range ◽  
Speed Performance ◽  
Self Tuning ◽  
Model Reference Adaptive

<span>Fuzzy logic controller (FLC) has shown excellent performance in dealing with the non-linearity and complex dynamic model of the induction motor. However, a conventional constant parameter FLC (CPFL) will not be able to provide–good coverage performance for a wide speed range operation with a single tuning parameter. Therefore, this paper proposed a self tuning mechanism FLC approach by model reference adaptive controller (ST-MRAC) to continuously allow to adjust the parameters. Due to real time hardware application, the dominant rules selection method for simplified rules has been implemented as part of the reducing computational burden. Experiment results validate a good performance of the ST-MRAC compared to the CPFL for the   speed performance in terms of the wide range of operations and disturbance showed remarkable performance.</span>

A Parametric Study of the Modified Model Reference Adaptive Control Scheme

1998 ◽  
Vol 120 (3) ◽  
pp. 814-821
Author(s):  
H. M. Sardar ◽  
M. Ahmadian
Keyword(s):  
Closed Loop ◽  
Simulation Analysis ◽  
Adaptive Controller ◽  
Loop System ◽  
Closed Loop System ◽  
Model Reference ◽  
Modified Model ◽  
Control Scheme ◽  
Inertial Nonlinearities ◽  
Model Reference Adaptive

The validity of the claim by many studies that the damping and stiffness forces can be ignored when designing a model reference adaptive controller, is examined. For a simple plant, the sensitivity of the closed loop system to the inertial, damping, and stiffness nonlinearities are investigated, through a simulation analysis. It is shown that the closed loop system is sensitive to the changes in the inertial nonlinearities, and relatively insensitive to variations in the damping and stiffness forces. This supports the assumption made in many previous studies.

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