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This paper proposes a new control structure for tasks where explicit disturbance compensation is not only critical for overcoming poor feedback performance but is also challenging due to the complexity and nonrepetitive nature of the interaction between the plant and the environment. The approach proposed uses a particular form of iterative learning control (ILC) to estimate the previous disturbances,...
Model uncertainty complicates most kinodynamic motion planning and control approaches due to their reliance on accurate forward prediction. If the model uncertainty is significant, a generated path or control strategy based on forward simulation of this model is potentially invalid and expensive to track (if possible). This paper explores the use of system identification/estimation to tune model parameters...
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