RECURSIVE LEAST SQUARES ESTIMATOR BASED ADAPTIVE SLIDING MODE CONTROLLER FOR AN AUTONOMOUS UNDERWATER VEHICLE

Date

2023-9-11

Author

ÇAKIR, Sertaç

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Mathematical models of underwater vehicles are highly nonlinear, coupled, and involves significant uncertainty. Therefore, a robust and comprehensive control strategy is required in autonomous underwater vehicle (AUV) autopilot design. In addition to this, obtaining the model parameters with computational fluid dynamics (CFD) analysis is most often too expensive and time consuming. Hence, an adaptive strategy, which may eliminate the need for CFD analysis, in control system design is deeply favorable. In this thesis: The attitude control of AUV is established robustly with a multi variable sliding mode controller (SMC). The well-known chattering phenomenon is solved with a proportional integral (PI) like boundary layer switching design. The hydrodynamic derivatives are estimated online with recursive least squares estimator (RLSE) which is integrated into the equivalent control term of SMC. Estimation, stability and tracking performances of the proposed method is ensured with simulations which are based on a high fidelity model of the vehicle and the environment. The parameter estimation performance is also demonstrated with a real underwater vehicle test data. As a result, the proposed method is proved to control the attitude of an AUV without any prior hydrodynamic derivative information.

Subject Keywords

autonomous, underwater vehicle, autopilot, adaptive, estimation, system identification, sliding mode control, recursive, least squares

URI

https://hdl.handle.net/11511/105603

Collections

Graduate School of Natural and Applied Sciences, Thesis