Multi Set-Point Explicit Model Predictive Control for Nonlinear Process Systems
Multi Set-Point Explicit Model Predictive Control for Nonlinear Process Systems
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DOI：
10.3390/pr9071156
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发表时间：
2021-07
期刊：
影响因子：
3.5
通讯作者：
Vassilis M. Charitopoulos;L. Papageorgiou;V. Dua
中科院分区：
文献类型：
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作者：
Vassilis M. Charitopoulos;L. Papageorgiou;V. Dua
在这篇文章中，我们介绍了一种新的框架设计的多设定点非线性显式控制器的过程系统工程问题的设定点被视为不确定的参数，同时在每个采样实例的动态系统的初始状态。为此，一类特殊的多参数非线性规划问题的不确定参数的约束和目标函数的成本系数的右手边的算法。该算法是基于计算代数方法的符号操作，使底层的多参数非线性程序的最优性条件的分析解决方案。所提出的算法的一个显着的属性是精确的计算，在一般非凸的，关键区域，结果在潜在的巨大的计算节省通过减少凸近似的关键区域的数量。
In this article, we introduce a novel framework for the design of multi set-point nonlinear explicit controllers for process systems engineering problems where the set-points are treated as uncertain parameters simultaneously with the initial state of the dynamical system at each sampling instance. To this end, an algorithm for a special class of multi-parametric nonlinear programming problems with uncertain parameters on the right-hand side of the constraints and the cost coefficients of the objective function is presented. The algorithm is based on computed algebra methods for symbolic manipulation that enable an analytical solution of the optimality conditions of the underlying multi-parametric nonlinear program. A notable property of the presented algorithm is the computation of exact, in general nonconvex, critical regions that results in potentially great computational savings through a reduction in the number of convex approximate critical regions.