One of the many lucrative marine industries is recreational SCUBA diving, having contributed over US$ 10 billion to the US gross product in 2011 alone. However, SCUBA diving is associated with a lot of potential hazards and inconveniences, hence it opens up the need for an autonomous diving assistant.

The main aim of this project is to develop a mathematical model of an underwater vehicle, and based on the model design a controller that can maintain leveled flight during horizontal plane motion, while performing well in station-keeping operation. This is challenging because underwater vehicle performance suffers a lot in underwater environment where environmental disturbances are imminent and usually unpredictable.

The mathematical model of the vehicle is developed by using sy...[ Read more ]

One of the many lucrative marine industries is recreational SCUBA diving, having contributed over US$ 10 billion to the US gross product in 2011 alone. However, SCUBA diving is associated with a lot of potential hazards and inconveniences, hence it opens up the need for an autonomous diving assistant.

The main aim of this project is to develop a mathematical model of an underwater vehicle, and based on the model design a controller that can maintain leveled flight during horizontal plane motion, while performing well in station-keeping operation. This is challenging because underwater vehicle performance suffers a lot in underwater environment where environmental disturbances are imminent and usually unpredictable.

The mathematical model of the vehicle is developed by using system identification method. This method finds the model that suits the underwater vehicle by comparing the measured controller response with simulated controller response. The model is validated by applying it to controllers with different gains. Rough model can be generated, and it is possible to describe the controller performance, but is not accurate enough to describe minute oscillations and vibrations.

Computed-torque controller is chosen due to the implementation simplicity and robustness. However, the controller’s gain cannot be tuned to accomodate various conditions, hence a fuzzy adaptive compensating controller is developed to complement it. The fuzzy adaptive controller takes force input in x and y direction and generate suitable output to compensate for horizontal plane motion. The implementation of the compensating controller improves the controller performance by over 60% in the same experiment.