4.6 Article

Robust optimal control for a batch nonlinear enzyme-catalytic switched time-delayed process with noisy output measurements

Journal

NONLINEAR ANALYSIS-HYBRID SYSTEMS
Volume 41, Issue -, Pages -

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.nahs.2021.101059

Keywords

Robust optimal control; Switched time-delayed system; Noisy output measurements; Auxiliary dynamical system

Funding

  1. National Natural Science Foundation of China [11901075, 51979034, 11771008, 11701063, 71831002, 11871039, 61773086]
  2. China Postdoctoral Science Foundation [2019M661073, 2019M651091]
  3. Natural Science Foundation of Liaoning Province in China (Doctoral Startup Foundation of Liaoning Province in China) [2020BS074]
  4. Fundamental Research Funds for the Central Universities, China [DUT20YG125]
  5. Australian Research Council [DP190103361]
  6. Natural Science Foundation of Shandong Province in China [ZR2017MA005, ZR2019MA031]
  7. Xinghai Project of Dalian Maritime University, China

Ask authors/readers for more resources

This paper considers a nonlinear switched time-delayed (NSTD) system with an unknown time-varying function in a batch culture. The goal is to estimate unknown quantities using noisy output measurements and biological robustness. The estimation problem is formulated as a robust optimal control problem governed by the NSTD system with continuous state inequality constraints, and approximated using a sequence of nonlinear programming subproblems.
In this paper, we consider a nonlinear switched time-delayed (NSTD) system with an unknown time-varying function describing the batch culture. The output measurements are noisy. According to the actual fermentation process, this time-varying function appears in the form of a piecewise-linear function with unknown kinetic parameters and switching times. The quantitative definition of biological robustness is given to overcome the difficulty of accurately measuring intracellular material concentrations. Our main goal is to estimate these unknown quantities by using noisy output measurements and biological robustness. This estimation problem is formulated as a robust optimal control problem (ROCP) governed by the NSTD system subject to continuous state inequality constraints. The ROCP is approximated as a sequence of nonlinear programming subproblems by using some techniques. Due to the highly complex nature of these subproblems, we propose a hybrid parallel algorithm, based on Nelder-Mead method, simulated annealing and the gradients of the constraint functions, for solving these subproblems. The paper concludes with simulation results. (C) 2021 Elsevier Ltd. All rights reserved.

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