1. Edward Polk II ET 494 Advisor: Dr. Cris

2. Introduction Submersibles are underwater machines with many applications including deep sea exploration and repairing critical underwater systems like the oil pipeline in the Deepwater Horizon spill. Handling such machines is a difficult task requiring several operators to operate a sophisticated control scheme. Autonomous stabilization would drastically reduce the workload for operating team and the magnitude of control station.

3. Objectives Design a miniaturized submersible. Use its thrusters to counteract the effect of drift or turbulent currents and remain stationary. Develop an adaptive control algorithm to perform this task autonomously.

4. Components Arduino Mega 2560 PVC pipe Arduino GY-521 MPU-6050 Module 3 axial gyroscope accelerometer stance tilt module Amico 1500 -10000RPM 3-12V High Torque DC Motors with Propeller L293 Quadruple Half-H Drivers

5. Previously Accomplished Milestones Research possible materials for project and select ones that are suitable for the submersible. Find an effective way to waterproof the motors. Construct and test the circuit with the motors, then the MPU-6050 module. Construct the current design model,develop a sample Arduino program to test the submersible in water. Present a working model that will be the basis of the next iteration of Senior Design.

6. Old Submersible

7. Old Circuit

8. Changed/Added Components Replace the Amico motors with Rule 500 gph bilge pumps. Replace L293 with TIP120. Added 50W 6ohm resistors. Added pool noodles. Replace Arduino Mega with Uno. Replaced 9V battery with PC power supply.

9. New Submersible

11. New Circuit

12. Circuit Inside of Pipe

13. PC power supply

14. Adaptive Control Algorithm The success of this project lies in the design of an effective control algorithm. Therefore a majority of time and effort will be allocated to researching and designing this algorithm. The type of method that I have chose is neural network. Neural networks are learning algorithms that work similarly to how the brain learns. They are utilized in applications such as speech recognition, object recognition, image retrieval and the ability to recommend products that a user would like.

15. Stabilization

21. Potential Neural Network

22. Completed Milestones Conduct more tests to ensure that it is waterproof and will remain that way and that the motors are powerful enough to overcome the forces applied to it. Conduct research for neural networks. Design a program that reads the displacement values and activates the appropriate motors. Prepare the final demonstration and deliver it to Dr. Cris.