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Iterative learning control for optimal multiple-point tracking | IEEE Conference Publication | IEEE Xplore

Iterative learning control for optimal multiple-point tracking


Abstract:

This paper presents a new optimization-based iterative learning control (ILC) framework for multiple-point tracking control. Conventionally, one demand prior to designing...Show More

Abstract:

This paper presents a new optimization-based iterative learning control (ILC) framework for multiple-point tracking control. Conventionally, one demand prior to designing ILC algorithms for such problems is to build a reference trajectory that passes through all given points at given times. In this paper, we produce output curves that pass close to the desired points without considering the reference trajectory. Here, the control signals are generated by solving an optimal ILC problem with respect to the points. As such, the whole process becomes simpler; key advantages include significantly decreasing the computational cost and improving performance. Our work is then examined in both continuous and discrete systems.
Date of Conference: 12-15 December 2011
Date Added to IEEE Xplore: 01 March 2012
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Conference Location: Orlando, FL, USA

References

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