Control of nonlinear biological systems by non–minimal state variable feedback

Taylor, C. James and Aerts, Jean-Marie (2014) Control of nonlinear biological systems by non–minimal state variable feedback. Statistics in Biosciences, 6 (2). pp. 290-313. ISSN 1867-1764

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We contrast biostatistical methods for optimal treatment determination with optimal control methodology, originally developed in the engineering literature but now used more widely. We describe non-minimal state space (NMSS) control methods for biological systems, with a particular focus on the use of state-dependent parameter models to represent system nonlinearities. Three examples are considered, namely the control of (i) a nonlinear forced logistic function implemented with a time-delay; (ii) athletic horse heart rate with potential application for training improvement; and (iii) a physically--based simulation model for the uptake of CO2 by plant leaves in response to light intensity, with application to closed-environment grow cells. Although all three examples have been extensively studied in the literature, the novelties of the present article are in the NMSS formulation and the application of a recently developed state-dependent (nonlinear) control algorithm. In the case of the leaf photosynthesis simulation, however, the linear NMSS algorithm yields satisfactory results, illustrating the inherent robustness of feedback.

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Journal Article
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Statistics in Biosciences
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19 Nov 2013 11:50
Last Modified:
22 Nov 2022 00:27