A Sliding Mode Approach-Based Adaptive Steering Control Algorithm for Path Tracking of Autonomous Mobility with Weighted Injection
The increasing complexity of mathematical models developed as part of the recent advancements in autonomous mobility platforms has led to an escalation in uncertainty. Despite the intricate nature of such models, the detection, decision, and control methods for autonomous mobility path tracking rema...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-10-01
|
| Series: | Machines |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2075-1702/11/10/972 |
| _version_ | 1797573137743740928 |
|---|---|
| author | Sehwan Kim Kwangseok Oh |
| author_facet | Sehwan Kim Kwangseok Oh |
| author_sort | Sehwan Kim |
| collection | DOAJ |
| description | The increasing complexity of mathematical models developed as part of the recent advancements in autonomous mobility platforms has led to an escalation in uncertainty. Despite the intricate nature of such models, the detection, decision, and control methods for autonomous mobility path tracking remain critical. This study aims to achieve path tracking based on pixel-based control errors without parameters in the mathematical model. The proposed approach entails deriving control errors from a multi-particle filter based on a camera, estimating the error dynamics coefficients through a recursive least squares (RLS) approach, and using the sliding mode approach and weighted injection to formulate a cost function that leverages the estimated coefficients and control errors. The resultant adaptive steering control expedites the convergence of control errors towards zero by determining the magnitude of the injection variable based on the control errors and the finite-time convergence condition. The efficacy of the proposed approach is evaluated through an S-curved and elliptical path using autonomous mobility equipped with a single steering and driving module. The results demonstrate the capability of the approach to reasonably track target paths through driving and steering control facilitated by a multi-particle filter and a lidar-based obstacle detection system. |
| first_indexed | 2024-03-10T21:05:28Z |
| format | Article |
| id | doaj.art-1803cf8ecc584da09159fc978c1f046b |
| institution | Directory Open Access Journal |
| issn | 2075-1702 |
| language | English |
| last_indexed | 2024-03-10T21:05:28Z |
| publishDate | 2023-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Machines |
| spelling | doaj.art-1803cf8ecc584da09159fc978c1f046b2023-11-19T17:08:50ZengMDPI AGMachines2075-17022023-10-01111097210.3390/machines11100972A Sliding Mode Approach-Based Adaptive Steering Control Algorithm for Path Tracking of Autonomous Mobility with Weighted InjectionSehwan Kim0Kwangseok Oh1School of ICT, Robotics & Mechanical Engineering, Hankyong National University, Anseong-si 17579, Republic of KoreaSchool of ICT, Robotics & Mechanical Engineering, Hankyong National University, Anseong-si 17579, Republic of KoreaThe increasing complexity of mathematical models developed as part of the recent advancements in autonomous mobility platforms has led to an escalation in uncertainty. Despite the intricate nature of such models, the detection, decision, and control methods for autonomous mobility path tracking remain critical. This study aims to achieve path tracking based on pixel-based control errors without parameters in the mathematical model. The proposed approach entails deriving control errors from a multi-particle filter based on a camera, estimating the error dynamics coefficients through a recursive least squares (RLS) approach, and using the sliding mode approach and weighted injection to formulate a cost function that leverages the estimated coefficients and control errors. The resultant adaptive steering control expedites the convergence of control errors towards zero by determining the magnitude of the injection variable based on the control errors and the finite-time convergence condition. The efficacy of the proposed approach is evaluated through an S-curved and elliptical path using autonomous mobility equipped with a single steering and driving module. The results demonstrate the capability of the approach to reasonably track target paths through driving and steering control facilitated by a multi-particle filter and a lidar-based obstacle detection system.https://www.mdpi.com/2075-1702/11/10/972adaptive steering controlsliding mode approachweighted injectionmulti-particle filterrecursive least squaresautonomous mobility |
| spellingShingle | Sehwan Kim Kwangseok Oh A Sliding Mode Approach-Based Adaptive Steering Control Algorithm for Path Tracking of Autonomous Mobility with Weighted Injection Machines adaptive steering control sliding mode approach weighted injection multi-particle filter recursive least squares autonomous mobility |
| title | A Sliding Mode Approach-Based Adaptive Steering Control Algorithm for Path Tracking of Autonomous Mobility with Weighted Injection |
| title_full | A Sliding Mode Approach-Based Adaptive Steering Control Algorithm for Path Tracking of Autonomous Mobility with Weighted Injection |
| title_fullStr | A Sliding Mode Approach-Based Adaptive Steering Control Algorithm for Path Tracking of Autonomous Mobility with Weighted Injection |
| title_full_unstemmed | A Sliding Mode Approach-Based Adaptive Steering Control Algorithm for Path Tracking of Autonomous Mobility with Weighted Injection |
| title_short | A Sliding Mode Approach-Based Adaptive Steering Control Algorithm for Path Tracking of Autonomous Mobility with Weighted Injection |
| title_sort | sliding mode approach based adaptive steering control algorithm for path tracking of autonomous mobility with weighted injection |
| topic | adaptive steering control sliding mode approach weighted injection multi-particle filter recursive least squares autonomous mobility |
| url | https://www.mdpi.com/2075-1702/11/10/972 |
| work_keys_str_mv | AT sehwankim aslidingmodeapproachbasedadaptivesteeringcontrolalgorithmforpathtrackingofautonomousmobilitywithweightedinjection AT kwangseokoh aslidingmodeapproachbasedadaptivesteeringcontrolalgorithmforpathtrackingofautonomousmobilitywithweightedinjection AT sehwankim slidingmodeapproachbasedadaptivesteeringcontrolalgorithmforpathtrackingofautonomousmobilitywithweightedinjection AT kwangseokoh slidingmodeapproachbasedadaptivesteeringcontrolalgorithmforpathtrackingofautonomousmobilitywithweightedinjection |