Enhanced Trajectory Tracking via Disturbance-Observer-Based Modified Sliding Mode Control

Trajectory tracking is a crucial aspect of controlling nonlinear systems and is an important area of research. Researchers have proposed several strategies to perform this task in the presence of perturbations, which are the sum of a system’s uncertainty, modeling errors, and external disturbances....

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Main Authors: Saad Jamshed Abbasi, Sangchul Lee
Format: Article
Language:English
Published: MDPI AG 2023-07-01
Series:Applied Sciences
Subjects:
Online Access:https://www.mdpi.com/2076-3417/13/14/8027
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author Saad Jamshed Abbasi
Sangchul Lee
author_facet Saad Jamshed Abbasi
Sangchul Lee
author_sort Saad Jamshed Abbasi
collection DOAJ
description Trajectory tracking is a crucial aspect of controlling nonlinear systems and is an important area of research. Researchers have proposed several strategies to perform this task in the presence of perturbations, which are the sum of a system’s uncertainty, modeling errors, and external disturbances. Nonlinear systems, such as robot manipulators, have complex dynamics, and deriving their exact mathematical models is a tedious task. Therefore, the objective of this research is to design a model-free form of control for such systems. To achieve this goal, a sliding mode control (SMC) with a proportional-integral-derivative (PID) sliding surface was designed and integrated with a saturation-function-based extended-state observer (ESO). In an extended-state observer (ESO), the primary concept is to define the system’s perturbation. The ESO estimates the system’s states and perturbation, including the known and unknown dynamics, uncertainties, and external disturbances, which are considered as perturbations. The estimated perturbation is used in a closed loop to cancel the actual perturbation. This perturbation-rejection technique improved the controller’s performance, resulting in reduced position error, reduced sensitivity to low-frequency elements of perturbation, and a small magnitude of switching gain. The designed control algorithm requires minimal information about the system, specifically position feedback, and, therefore, there is no need to identify the system parameters. A mathematical analysis of the designed algorithm was performed in detail, and the algorithm was compared with the existing ESO-based SMC algorithm. Simulations were conducted using MATLAB/SimMechanics on two different systems, and the comparison results validated the performance of the designed algorithm in comparison to previous research.
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spelling doaj.art-04c093ade5c24962aaa46f91d40659df2023-11-18T18:07:07ZengMDPI AGApplied Sciences2076-34172023-07-011314802710.3390/app13148027Enhanced Trajectory Tracking via Disturbance-Observer-Based Modified Sliding Mode ControlSaad Jamshed Abbasi0Sangchul Lee1Department of Smart Air Mobility, Korea Aerospace University, Goyang 10540, Republic of KoreaDepartment of Smart Air Mobility, Korea Aerospace University, Goyang 10540, Republic of KoreaTrajectory tracking is a crucial aspect of controlling nonlinear systems and is an important area of research. Researchers have proposed several strategies to perform this task in the presence of perturbations, which are the sum of a system’s uncertainty, modeling errors, and external disturbances. Nonlinear systems, such as robot manipulators, have complex dynamics, and deriving their exact mathematical models is a tedious task. Therefore, the objective of this research is to design a model-free form of control for such systems. To achieve this goal, a sliding mode control (SMC) with a proportional-integral-derivative (PID) sliding surface was designed and integrated with a saturation-function-based extended-state observer (ESO). In an extended-state observer (ESO), the primary concept is to define the system’s perturbation. The ESO estimates the system’s states and perturbation, including the known and unknown dynamics, uncertainties, and external disturbances, which are considered as perturbations. The estimated perturbation is used in a closed loop to cancel the actual perturbation. This perturbation-rejection technique improved the controller’s performance, resulting in reduced position error, reduced sensitivity to low-frequency elements of perturbation, and a small magnitude of switching gain. The designed control algorithm requires minimal information about the system, specifically position feedback, and, therefore, there is no need to identify the system parameters. A mathematical analysis of the designed algorithm was performed in detail, and the algorithm was compared with the existing ESO-based SMC algorithm. Simulations were conducted using MATLAB/SimMechanics on two different systems, and the comparison results validated the performance of the designed algorithm in comparison to previous research.https://www.mdpi.com/2076-3417/13/14/8027trajectory trackingsliding mode controlnonlinear systemsperturbation rejectiondisturbance observer
spellingShingle Saad Jamshed Abbasi
Sangchul Lee
Enhanced Trajectory Tracking via Disturbance-Observer-Based Modified Sliding Mode Control
Applied Sciences
trajectory tracking
sliding mode control
nonlinear systems
perturbation rejection
disturbance observer
title Enhanced Trajectory Tracking via Disturbance-Observer-Based Modified Sliding Mode Control
title_full Enhanced Trajectory Tracking via Disturbance-Observer-Based Modified Sliding Mode Control
title_fullStr Enhanced Trajectory Tracking via Disturbance-Observer-Based Modified Sliding Mode Control
title_full_unstemmed Enhanced Trajectory Tracking via Disturbance-Observer-Based Modified Sliding Mode Control
title_short Enhanced Trajectory Tracking via Disturbance-Observer-Based Modified Sliding Mode Control
title_sort enhanced trajectory tracking via disturbance observer based modified sliding mode control
topic trajectory tracking
sliding mode control
nonlinear systems
perturbation rejection
disturbance observer
url https://www.mdpi.com/2076-3417/13/14/8027
work_keys_str_mv AT saadjamshedabbasi enhancedtrajectorytrackingviadisturbanceobserverbasedmodifiedslidingmodecontrol
AT sangchullee enhancedtrajectorytrackingviadisturbanceobserverbasedmodifiedslidingmodecontrol