MRAC for towed auv model

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Johannes
Johannes il 3 Mag 2024
Risposto: Kothuri il 23 Mag 2024
Hi, i have a towed auv, which can actively affect its depth and roll angle. Is the Mrac control approach suitable for active roll stabilization due to its adaption to unknown disturbances(wave, current, etc)? Second: is it worth running nonlinear greybox estimation for the system dynamics (given the math. Dynamic model) due to some unknown values (assuming Sensors measuring nesr perfect data) and use the optained model for the mrac and a optimized Version of this model (tuned frequency and natural damping using poleplacement solution) as ref model?

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Kothuri
Kothuri il 23 Mag 2024
  • As towed AUV (Autonomous Underwater Vehicle) must deal with complex, unpredictable underwater environments, Model Reference Adaptive Control (MRAC) is a suitable approach for active roll stabilization in environments with unknown disturbances such as waves and currents. The main advantage of MRAC is its ability to adapt the controller parameters in real-time to match the performance of a reference model, even in the presence of uncertainties and external disturbances. This adaptability makes it particularly suitable for applications like AUVs, where the operating conditions can vary significantly and are not always predictable.
You can refer the below documentation on MRAC.
  • Nonlinear Grey-Box estimation involves a model that contains a mix of known and unknown components. Due to the complex nature of underwater dynamics and the potential for unknown variables in the design and environmental interaction of an AUV, nonlinear grey-box estimation can be a powerful tool for improving the understanding of the system's behaviour.
You can refer the below link on Modeling a Vehicle Dynamics System using Non-Linear Grey-Box modelling
The estimated model can provide a more accurate representation of the AUV's dynamics, which is crucial for designing effective control strategies. And optimizing this model (by tuning frequency and natural damping through pole placement) to serve as the reference model in the MRAC framework can further enhance control performance.
Hope this solves your doubt.

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