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.

在本文中，我们考虑具有描述批次文化的未知时变函数的非线性切换时滞（NSTD）系统。输出测量结果很嘈杂。根据实际的发酵过程，该时变函数以分段线性函数的形式出现，其动力学参数和切换时间未知。给出了生物学鲁棒性的定量定义，以克服精确测量细胞内物质浓度的困难。我们的主要目标是通过使用噪声输出测量值和生物学鲁棒性来估计这些未知量。将该估计问题表述为受连续状态不等式约束的NSTD系统支配的鲁棒最优控制问题（ROCP）。通过使用某些技术，ROCP被近似为一系列非线性编程子问题。由于这些子问题的高度复杂性，我们提出了一种基于Nelder–Mead方法，模拟退火和约束函数梯度的混合并行算法来解决这些子问题。本文最后给出了仿真结果。