Robust Diving and Composite Path Tracking Control of an Autonomous Underwater Vehicle
- Spandan Roy (CSIR-Central Mechanical Engineering Research Institute) | Sambhunath Nandy (CSIR-Central Mechanical Engineering Research Institute) | Ranjit Ray (CSIR-Central Mechanical Engineering Research Institute) | Siva Ram Krishna Vadali (CSIR-Central Mechanical Engineering Research Institute) | Sankar Nath Shome (CSIR-Central Mechanical Engineering Research Institute)
- Document ID
- International Society of Offshore and Polar Engineers
- International Journal of Offshore and Polar Engineering
- Publication Date
- December 2015
- Document Type
- Journal Paper
- 305 - 313
- 2015. The International Society of Offshore and Polar Engineers
- AUV, diving, time delay control, robust control, sliding mode control, path tracking
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- 43 since 2007
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Autonomous Underwater Vehicles (AUVs) are becoming indispensable for the maritime industry and defense applications. The nonlinear, time-varying, and highly coupled dynamics of AUVs, along with the parametric uncertainties and unmodeled dynamics, make the design of efficient controllers a hard task. This article explores a robust control strategy that aims at providing better tracking accuracy by reducing the switching gain in order to reduce chattering and the control error bandwidth. The performance of the proposed controller is demonstrated through rigorous simulation on an experimentally validated AUV, and superior path tracking performance is noted against sliding mode and time delay control methodologies under various uncertain conditions.
Autonomous Underwater Vehicles (AUVs) have received great attention in the last two decades from the maritime industry and defense applications due to the enormous need for these automated electromechanical systems. AUVs are very convenient to use during a voyage in the depths of the sea where situations are difficult for human deployment. As a result, a great deal of research is commonly focused on designing control methodologies that allow these systems to execute the assigned tasks often in unstructured and unpredictable environments. Needless to say, the difficulty in controlling AUVs not only resides in the highly nonlinear and coupled dynamics but also gets greatly enhanced due to model uncertainty and unknown disturbances. To illustrate the scenario, the modeling of the hydrodynamic parameters of an AUV is an extremely challenging task. Also, the deviation of the center of mass (COM) for the addition of payloads for different applications and environmental hazards, such as uncertain ocean currents, renders control of such mobile robotic systems highly tedious.
Well-known linear control techniques are inadequate to tackle the highly nonlinear, coupled, and time-varying dynamics of the AUVs and thereby to provide acceptable tracking performance. In a real-life scenario, the physical presence of uncertain parameters is inevitable, and the modeling of all such parameters is not always feasible. This makes the realization of the conventional nonlinear feedback linearization control law (i.e., the computed torque techniques) difficult as it requires precise knowledge of the hardware parameters of the system such as the mass and inertia parameters, COM, and hydrodynamic parameters. The global research community has adopted various nonlinear control techniques to accurately drive the AUVs, which are subjected to uncertainties and disturbances, along a defined path. Adaptive control and robust control strategies are the most commonly used techniques.
Cristi and Healey (1989) reported a model-based adaptive controller linearizing the vehicle dynamics within the limited operating range. A recursive least square method for parameter estimation and a pole placement technique for controller development were used.
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