Robust LPV Fault Diagnosis Using the Set-Based Approach for Autonomous Ground Vehicles
This paper proposes a robust fault diagnosis method for Autonomous Ground Vehicles (AGVs) modeled as a Linear Parameter Varying (LPV) system with bounded uncertainties. The proposed approach combines the zonotope-based Set-Membership Approach (SMA) and Set Invariance Approach (SIA). Firstly, an onli...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión aceptada para publicación |
| Fecha de publicación: | 2024 |
| País: | España |
| Institución: | Consejo Superior de Investigaciones Científicas (CSIC) |
| Repositorio: | DIGITAL.CSIC. Repositorio Institucional del CSIC |
| OAI Identifier: | oai:digital.csic.es:10261/377665 |
| Acceso en línea: | http://hdl.handle.net/10261/377665 https://api.elsevier.com/content/abstract/scopus_id/85192744858 |
| Access Level: | acceso abierto |
| Palabra clave: | Autonomous ground vehicles Fault diagnosis LPV Minimum detectable fault Minimum isolable fault Set invariance approach Set-membership approach |
| Sumario: | This paper proposes a robust fault diagnosis method for Autonomous Ground Vehicles (AGVs) modeled as a Linear Parameter Varying (LPV) system with bounded uncertainties. The proposed approach combines the zonotope-based Set-Membership Approach (SMA) and Set Invariance Approach (SIA). Firstly, an online fault detection strategy based on zonotopic set-membership state estimation is introduced, where the optimal observer gain is calculated offline by solving LMI optimization problems. To characterize the Minimum Detectable Fault (MDF) and Minimum Isolable Fault (MIF), the invariant residual sets are first obtained for the system operated in healthy and faulty modes. The proposed method relies on the propagation of the zonotopic state estimation error in steady state based on SIA. Then, MDF and MIF are characterized for several types of faults by solving optimization problems subject to set separation conditions. Finally, experiment validations using a prototype vehicle are performed to illustrate the effectiveness of the proposed approach. |
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