Control Allocation for Underwater Snake Robots using Optimization Methods
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- Institutt for marin teknikk 
Although the concept of underwater vehicles has existed for a very long time, the technologywithin the field has progressed substantially over the recent decades. As more and more oil andgas installations and operations are performed subsea, the need for more developed underwatervehicles is still present. A new concept which has the potential to fulfill these demands is theUnderwater Underwater Snake Robot. The fact that the robot is shaped as a snake makes itideal for moving in high viscosity environments such as water. In addition, the robot s abilityto alter configuration provides a large workspace, and its slender and articulate body allows therobot to access narrow spaces. The fact that the underwater snake robot is, itself, a manipulatorarm capable of performing light intervention tasks, makes it a powerful tool. In this thesis, methods for thrust allocation for underwater snake robots are evaluated. Twoiterative methods, using linear and quadratic programming, are presented, developed and implemented.This is also done for an explicit method for constrained thrust allocation, using redistributedpseudo-inverse. The methods are implemented into an existing underwater snakerobot simulation model in Matlab/SIMULINK. Simulations are performed for unconstrainedand constrained thrust allocation, simulating planar and thee-dimensional motion. In the unconstrainedcase, simulations are also performed using a pre-implemented standard dampedinverse algorithm. This is done in order to compare thrust allocation algorithm performances. It is found that all developed algorithms produce satisfactory simulation results, althoughsome variations in performance is found. The linear programming algorithm produces a smallerror between commanded and actual thrust, but tends to favor using a low amount of thrusters,which is not ideal. In the constrained case, the performance of this algorithm is better. The redistributed pseudo-inverse algorithm produces a large error compared to the othermethods. The performance is therefore found to be sub-optimal. The quadratic programmingalgorithm produces low errors for all simulation cases. The algorithm also tends to distributethe commanded thrust more evenly amongst the thrusters. This is a significant up-side as itreduces wear and tear on the thrusters. Thus, it is concluded that the quadratic programming algorithm for thrust allocation producesthe most satisfactory results, although all thrust allocation methods have proven to beviable for use on underwater snake robots.