Abstract
The performance of a real time implementation of a digital control algorithm especially under a high sampling rate is affected by arithmetic errors caused by finite word-length arithmetic. The effects of these numerically induced errors can be measured both in terms of the sensitivity of the closed-loop performance due to changes in the coefficients of the control algorithm, and the effect of internal “noise” resulting from roundoff errors on the controller states. The least sensitive structures generally have the highest complexity in terms of the number of arithmetic operations required to compute the next controller output, while the most sensitive structures are often the least complex. A new class of low complexity algorithms is presented, which have only moderate complexity. In addition, it is shown how a software modification can eliminate the occurrence of internal arithmetic overflow, which are usually present in a conventional fixed-point implementation.
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Williamson, D. (2001). Implementation of a Class of Low Complexity, Low Sensitivity Digital Controllers Using Adaptive Fixed-Point Arithmetic. In: Istepanian, R.S.H., Whidborne, J.F. (eds) Digital Controller Implementation and Fragility. Advances in Industrial Control. Springer, London. https://doi.org/10.1007/978-1-4471-0265-6_4
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DOI: https://doi.org/10.1007/978-1-4471-0265-6_4
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