Paper Info
Title
Adaptive Vrft Based On Mfac For The Speed Control Of Pmdc Motor
Abstract
The significance of mathematical modelling in the classical control theory cannot be denied. However, the nonlinear system modelling is more complex than linear modelling and sometimes it is challenging to produce a nonlinear mathematical model of the system. The proposed work is mainly focused on data-driven virtual reference feedback tuning (VRFT) control combined with a model free adaptive control (MFAC) algorithm. The basic control structure of the VRFT system uses a close loop model as a reference. However, the input and output data model of the closed loop linear system is linearized in tight format. The reference model output error and the system expected output error are used as a control input. The estimated value of the pseudo partial derivative (PPD) in the past time is introduced to the new control law to improve the utilization rate of PPD. The whole performance of the controller design is essentially data driven and it does not demand any prior information about the system model. The VRFT-based MFA control system is applied to speed control of the permanent magnet DC motor in the Simulink platform. Moreover, the simulation results show that 8.6% speed tracking error is reduced using the proposed control algorithm as compared to VRFT and 4.7% is reduced as compared to MFA-based algorithms.
Year
DOI
Venue
2017
10.2316/Journal.201.2017.2.201-2775
CONTROL AND INTELLIGENT SYSTEMS
Keywords
Field
DocType
Permanent magnet DC motor (PMDC), model free adaptive control (MFAC), virtual reference feedback tuning (VRFT), pseudo partial derivative (PPD)
Control theory,Control engineering,Mathematics,Electronic speed control
Journal
Volume
Issue
ISSN
45
2
1480-1752
Citations 
PageRank 
References 
0
0.34
0
Authors
3
Name
Order
Citations
PageRank
Rana Javed Masood100.34
Dao Bo Wang2215.92
Muhammad Farhan Manzoor311.04