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Learning by observation is a useful goal for humanoid robots that strive for human-like motion. Over time the movements and actions of these robots are likely to require modification for different scenarios and environments. Therefore being able to `teach' the robot new tasks and motions without tedious programming is highly useful. The operational space formulation is a highly elegant robot manipulator...
This paper deals with robust iterative learning control design for uncertain single-input-single-output linear time-invariant systems. The design procedure is based upon solving the robust performance condition using the Youla parameterization and the mu-synthesis approach to obtain a feedback controller. Thereafter, a convergent iterative learning law is obtained by using the performance weighting...
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