Theoretical and Experimental Studies of Iterative Learning control of Underwater robot manipulators

Abstract

On underwater robot manipulators, high speed and high precision are basic requirements in order to improve efficiency of operations. To satisfy these requirements, feedforward control inputs are crucial. For making feedforward inputs, one of the methods is to estimate all parameters of underwater robot dynamics. However, parameter estimation of hydrodynamic coefficients is very difficult because the dynamics is complicated. To overcome such a difficulty, we apply iterative learning control to underwater robots. In this paper, we theoretically discuss the performance of iterative learning control for underwater robot manipulators. Moreover, the effectiveness of the learning control is experimentally verified through several experimental results.