Abstract
From a viewpoint of integrating control and scheduling, the impact of resource availability constraints on the implementation of iterative optimal control (IOC) algorithms is considered. As a novel application in the emerging field of feedback scheduling, fuzzy technology is employed to construct a feedback scheduler intended for anytime IOC applications. Thanks to the anytime nature of the IOC algorithm, it is possible to abort the optimization routine before it reaches the optimum. The maximum iteration number within the IOC algorithm is dynamically adjusted to achieve a desired CPU utilization level. Thus a tradeoff is done between the available CPU time and the quality of control. Preliminary simulation results argue that the proposed approach is effective in managing the inherent uncertainty in control task execution and delivers better performance than traditional IOC algorithm in computing resource constrained environments.
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Xia, F., Sun, Y. (2005). Anytime Iterative Optimal Control Using Fuzzy Feedback Scheduler. In: Khosla, R., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2005. Lecture Notes in Computer Science(), vol 3682. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11552451_46
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DOI: https://doi.org/10.1007/11552451_46
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28895-4
Online ISBN: 978-3-540-31986-3
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