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Optimal Control of a MIMO Bioreactor System Using Direct Approach
International Journal of Control, Automation and Systems ( IF 2.5 ) Pub Date : 2021-01-09 , DOI: 10.1007/s12555-020-0058-9
Abolfazl Simorgh , Abolhassan Razminia , Saleh Mobayen , Dumitru Baleanu

In this paper, the optimal control of a continuous type bioreactor with multi-input-multi-output signals is presented for the two active phases: growth and stationary. The underlying criterion to be minimized generalizes the classic quadratic forms to address some crucial objectives in controlling the bioreactor. In particular, the protection of actuators against fast switching in the controller output is considered by including a weighting term of the control signal derivatives. The direct optimal control approach is used to carry out the optimization in the presence of various limiting constraints. Direct methods are based on transcribing the infinite-dimensional problem to a finite-dimensional one. In this manuscript, direct single shooting and trapezoidal collocation methods are used for transcription, and the successive quadratic programming method is employed to solve the resulting nonlinear programming problem. It is shown that the trapezoidal method is an effective method for controlling the bioreactor in all the active phases, whereas the single shooting fails in dealing with the unstable one (i.e., growth). To analyze solutions in a more accurate manner, an auxiliary criterion is defined, and then the cheap control analysis is studied. The convergence to the lowest value of the auxiliary cost function and the effects on the optimal state and control trajectories are then examined by varying cheap parameters. Several numerical simulations support the presented theoretical formulation.

中文翻译:

使用直接方法优化控制 MIMO 生物反应器系统

在本文中,针对两个活跃阶段:生长阶段和静止阶段,提出了具有多输入多输出信号的连续式生物反应器的优化控制。要最小化的基本标准概括了经典的二次形式,以解决控制生物反应器的一些关键目标。特别地,通过包括控制信号导数的加权项来考虑保护执行器免于控制器输出中的快速切换。直接优化控制方法用于在存在各种限制约束的情况下进行优化。直接方法基于将无限维问题转化为有限维问题。在这篇手稿中,使用直接单拍和梯形搭配的方法进行转录,并采用逐次二次规划方法解决由此产生的非线性规划问题。结果表明,梯形法是控制生物反应器所有活性阶段的有效方法,而单射无法处理不稳定阶段(即生长)。为了以更准确的方式分析解决方案,定义了一个辅助准则,然后研究了廉价控制分析。然后通过改变廉价参数检查辅助成本函数的最低值的收敛以及对最佳状态和控制轨迹的影响。几个数值模拟支持提出的理论公式。结果表明,梯形法是控制生物反应器所有活性阶段的有效方法,而单射无法处理不稳定阶段(即生长)。为了以更准确的方式分析解决方案,定义了一个辅助准则,然后研究了廉价控制分析。然后通过改变廉价参数检查辅助成本函数的最低值的收敛以及对最佳状态和控制轨迹的影响。几个数值模拟支持提出的理论公式。结果表明,梯形法是控制生物反应器所有活性阶段的有效方法,而单射无法处理不稳定阶段(即生长)。为了以更准确的方式分析解决方案,定义了一个辅助准则,然后研究了廉价控制分析。然后通过改变廉价参数检查辅助成本函数的最低值的收敛以及对最佳状态和控制轨迹的影响。几个数值模拟支持提出的理论公式。然后通过改变廉价参数检查辅助成本函数的最低值的收敛以及对最佳状态和控制轨迹的影响。几个数值模拟支持提出的理论公式。然后通过改变廉价参数检查辅助成本函数的最低值的收敛以及对最佳状态和控制轨迹的影响。几个数值模拟支持提出的理论公式。
更新日期:2021-01-09
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