scholarly journals Real-coded Genetic Algorithm for system identification and tuning of a modified Model Reference Adaptive Controller for a hybrid tank system

2013 ◽  
Vol 37 (6) ◽  
pp. 3829-3847 ◽  
Author(s):  
K. Asan Mohideen ◽  
G. Saravanakumar ◽  
K. Valarmathi ◽  
D. Devaraj ◽  
T.K. Radhakrishnan
Keyword(s):  
Genetic Algorithm ◽  
System Identification ◽  
Adaptive Controller ◽  
Model Reference ◽  
Modified Model ◽  
Real Coded Genetic Algorithm ◽  
Tank System ◽  
Model Reference Adaptive

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.

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.

scholarly journals A Modified Model Reference Adaptive Controller (M-MRAC) Using an Updated MIT-Rule for the Altitude of a UAV

Electronics ◽  
2020 ◽  
Vol 9 (7) ◽  
pp. 1104
Author(s):  
Julian Rothe ◽  
Jasper Zevering ◽  
Michael Strohmeier ◽  
Sergio Montenegro
Keyword(s):  
Adaptive Controller ◽  
Massachusetts Institute Of Technology ◽  
Model Reference ◽  
Adaptive Controllers ◽  
Modified Model ◽  
Altitude Control ◽  
Institute Of Technology ◽  
The Stability ◽  
The University ◽  
Model Reference Adaptive

Unmanned Aerial Vehicles (UAVs) are playing an increasingly important role in a wide variety of areas and the range of applications increases daily, which can also be seen in the research of the topic. At the University of Wuerzburg drones are to be used in a project, where the aim is to catch possibly dangerous UAVs in mid air using a net, carried by two drones. This very special scenario poses new problems to the control of the drones, so that traditionally used Proportional-Integral-Differential (PID) controllers are no longer sufficient. Therefore a model-based adaption mechanism was chosen to be used to control the altitude of the drones. Though adaption based controllers have been used in the field of drone research before, the existing algorithms had to be modified to work with the special conditions of the altitude control of UAVs. The design and implementation of the modified Model Reference Adaptive Controllers (MRACs) with an updated Massachusetts Institute of Technology (MIT)-rule will be presented in this work. The behavior of the drones with and without the adaption as well as the changes to the original MRAC are then compared in simulation as well as on a real system and show very promising results in further improving the stability of the altitude control of the drones.

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