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For controlling Unmanned Underwater Vehicles (UUVs) in deep water, Proportional-Integral-Derivative (PID) control has previously been proposed. Disturbances due to waves are minimal at high depths, so PID provides an acceptable level of control for performing tasks such as station-keeping. In shallow water, disturbances from waves are considerably larger and thus station-keeping performance naturally degrades. The time delay in the response of the thrusters to the control input is critical to the accuracy of station keeping; here, a numerical assessment is detailed on the accuracy in station keeping of a commercial Remotely Operated Vehicle (ROV) when subjected to various wave disturbances while operating at various depths. The results display a maximum positional error increase of 69% compared to an ideal case where the thrust output is instantaneous, when operating at a 15m depth and subject to an irregular sea state of significant height 5.404m. Our analysis provides a narrow range of operational conditions within which it is deemed safe to use PID for station keeping in waves. This provides evidence that in order to employ UUVs outside of the deep water scenario, better predictive-based control is essential.
|Title of host publication||2020 Global Oceans 2020|
|Subtitle of host publication||Singapore - U.S. Gulf Coast|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Publication status||E-pub ahead of print - 9 Apr 2021|
|Event||2020 Global Oceans: Singapore - U.S. Gulf Coast, OCEANS 2020 - Biloxi, United States|
Duration: 5 Oct 2020 → 30 Oct 2020
|Name||2020 Global Oceans 2020: Singapore - U.S. Gulf Coast|
|Conference||2020 Global Oceans: Singapore - U.S. Gulf Coast, OCEANS 2020|
|Period||5/10/20 → 30/10/20|
- shallow water
- station keeping
- thruster dynamics
- underwater robotics
- remotely operated vehicles
FingerprintDive into the research topics of 'Impact of Thruster Dynamics on the Feasibility of ROV Station Keeping in Waves'. Together they form a unique fingerprint.
A nonlinear model predictive controller for remotely operated underwater vehicles with disturbance rejectionCao, Y., Li, B., Li, Q., Stokes, A., Ingram, D. & Kiprakis, A., 31 Aug 2020, In: IEEE Access. 8, p. 158622-158634 13 p.
Research output: Contribution to journal › Article › peer-reviewOpen AccessFile
Walker, K., Stokes, A., Kiprakis, A. & Giorgio-Serchi, F., 17 Apr 2020. 2 p.
Research output: Contribution to conference › Paper › peer-reviewOpen AccessFile