M. Herrera-Sarellano and S.M. Ratchev (UK)
Position and force control, iterativelearning, micro actuators, MEMS and sensors.
Non linearity and hysteresis are inherent properties of smart micro actuators and they are considered as major defects due to the limitation of motion accuracy that cause. During manipulation of very small objects, force control is a very critical requirement to perform high precision assembly operations. This paper presents Iterative learning control (ILC) approach to improve the positioning/force tracking accuracy of smart micro actuators. In this context, the learning operator is defined as a variable factor which is alterable according to previous trial output and the fit curve of hysteresis response of smart micro actuators. The work so far has been focused on the theoretical development of the model and positioning/force control strategy. The initial results suggest that there are significant advantages that could be gained in using a dual ILC concept for positioning and force control in terms of tracking accuracy with very fast convergence speed and robustness against unpredictable disturbances and perturbations.
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