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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Burke, M. |
| Copyright Year | 2012 |
| Description | Author affiliation: Mobile Intelligent Autonomous Systems research group of the CSIR, South Africa (Burke, M.) |
| Abstract | This work presents a model predictive path-following controller, which incorporates adaptive slip estimation for a tracked vehicle. Tracked vehicles are capable of manoeuvring in highly variable and uneven terrain, but difficulties in their control have traditionally limited their use as autonomous platforms. Attempts to compensate for slip in environments typically require that both the forward and rotational velocities of a platform be determined, but this can be challenging. This paper shows that it is possible to estimate vehicle traction using only a rate gyroscope, by providing a suitable adaptive least squares estimator to do so. An approach to generating slip compensating controls when platform velocity constraints are applied is also presented. The approach is controller independent, but we make use of a model predictive controller, vulnerable to the effects of model-plant mismatch, to highlight the efficacy of the proposed estimation and compensation. Path following results using a mixture model to generate feasible slip values are presented, and show a significant increase in controller performance. |
| Starting Page | 97 |
| Ending Page | 102 |
| File Size | 608690 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781467314039 |
| ISSN | 10504729 |
| e-ISBN | 9781467314053 |
| e-ISBN | 9781467314046 |
| DOI | 10.1109/ICRA.2012.6224684 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-05-14 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Vehicles Adaptation models Predictive models Estimation Tracking Kinematics Gyroscopes |
| Content Type | Text |
| Resource Type | Article |
| Subject | Artificial Intelligence Control and Systems Engineering Electrical and Electronic Engineering Software |
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