Kalman Filter and Variants for Estimation in 2DOF Serial Flexible Link and Joint Using Fractional Order PID Controller
Robotic manipulators have been widely used in industries, mainly to move tools into different specific positions. Thus, it has become necessary to have accurate knowledge about the tool position using forward kinematics after accessing the angular locations of limbs. This paper presents a simulation...
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doaj-4fecfbe2634d460abdc128e1b2574c232021-08-06T15:18:22ZengMDPI AGApplied Sciences2076-34172021-07-01116693669310.3390/app11156693Kalman Filter and Variants for Estimation in 2DOF Serial Flexible Link and Joint Using Fractional Order PID ControllerSagar Gupta0Abhaya Pal Singh1Dipankar Deb2Stepan Ozana3Institute of Infrastructure Technology Research and Management, Ahmedabad 380026, IndiaDepartment of Engineering, University of Sannio, Piazza Roma 21, 82100 Benevento, ItalyInstitute of Infrastructure Technology Research and Management, Ahmedabad 380026, IndiaDepartment of Cybernetics and Biomedical Engineering, Faculty of Electrical Engineering and Computer Science, VSB-Technical University of Ostrava, 17. Listopadu 2172/15, 708 00 Ostrava-Poruba, Czech RepublicRobotic manipulators have been widely used in industries, mainly to move tools into different specific positions. Thus, it has become necessary to have accurate knowledge about the tool position using forward kinematics after accessing the angular locations of limbs. This paper presents a simulation study in which an encoder attached to the limbs gathers information about the angular positions. The measured angles are applied to the Kalman Filter (KF) and its variants for state estimation. This work focuses on the use of fractional order controllers with a Two Degree of Freedom Serial Flexible Links (2DSFL) and Two Degree of Freedom Serial Flexible Joint (2DSFJ) and undertakes simulations with noise and a square wave as input. The fractional order controllers fit better with the system properties than integer order controllers. The KF and its variants use an unknown and assumed process and measurement noise matrices to predict the actual data. An optimisation problem is proposed to achieve reasonable estimations with the updated covariance matrices.https://www.mdpi.com/2076-3417/11/15/6693Serial Flexible LinkSerial Flexible Jointinteger order PIDfractional order PID state estimationKalman FilterUnscented Kalman Filter |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Sagar Gupta Abhaya Pal Singh Dipankar Deb Stepan Ozana |
spellingShingle |
Sagar Gupta Abhaya Pal Singh Dipankar Deb Stepan Ozana Kalman Filter and Variants for Estimation in 2DOF Serial Flexible Link and Joint Using Fractional Order PID Controller Applied Sciences Serial Flexible Link Serial Flexible Joint integer order PID fractional order PID state estimation Kalman Filter Unscented Kalman Filter |
author_facet |
Sagar Gupta Abhaya Pal Singh Dipankar Deb Stepan Ozana |
author_sort |
Sagar Gupta |
title |
Kalman Filter and Variants for Estimation in 2DOF Serial Flexible Link and Joint Using Fractional Order PID Controller |
title_short |
Kalman Filter and Variants for Estimation in 2DOF Serial Flexible Link and Joint Using Fractional Order PID Controller |
title_full |
Kalman Filter and Variants for Estimation in 2DOF Serial Flexible Link and Joint Using Fractional Order PID Controller |
title_fullStr |
Kalman Filter and Variants for Estimation in 2DOF Serial Flexible Link and Joint Using Fractional Order PID Controller |
title_full_unstemmed |
Kalman Filter and Variants for Estimation in 2DOF Serial Flexible Link and Joint Using Fractional Order PID Controller |
title_sort |
kalman filter and variants for estimation in 2dof serial flexible link and joint using fractional order pid controller |
publisher |
MDPI AG |
series |
Applied Sciences |
issn |
2076-3417 |
publishDate |
2021-07-01 |
description |
Robotic manipulators have been widely used in industries, mainly to move tools into different specific positions. Thus, it has become necessary to have accurate knowledge about the tool position using forward kinematics after accessing the angular locations of limbs. This paper presents a simulation study in which an encoder attached to the limbs gathers information about the angular positions. The measured angles are applied to the Kalman Filter (KF) and its variants for state estimation. This work focuses on the use of fractional order controllers with a Two Degree of Freedom Serial Flexible Links (2DSFL) and Two Degree of Freedom Serial Flexible Joint (2DSFJ) and undertakes simulations with noise and a square wave as input. The fractional order controllers fit better with the system properties than integer order controllers. The KF and its variants use an unknown and assumed process and measurement noise matrices to predict the actual data. An optimisation problem is proposed to achieve reasonable estimations with the updated covariance matrices. |
topic |
Serial Flexible Link Serial Flexible Joint integer order PID fractional order PID state estimation Kalman Filter Unscented Kalman Filter |
url |
https://www.mdpi.com/2076-3417/11/15/6693 |
work_keys_str_mv |
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