کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4998430 1460351 2017 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Globally optimal nonlinear model predictive control based on multi-parametric disaggregation
ترجمه فارسی عنوان
کنترل پیش بینی کننده مدل غیر خطی جهانی به طور کلی براساس تجزیه چند پارامتری
کلمات کلیدی
کنترل پیش بینی کننده مدل غیر خطی جهانی مطلوب، تجزیه چند پارامتری، بهینه سازی جهانی،
موضوعات مرتبط
مهندسی و علوم پایه مهندسی شیمی تکنولوژی و شیمی فرآیندی
چکیده انگلیسی
Nonlinear model predictive control is appropriate for controlling highly nonlinear processes, particularly when operating conditions change frequently. If the problem is nonconvex, the controller must lead the process to a global, rather than a local optimum. This work deals with computation of the control actions which lead to the global optimum via the normalized multi-parametric disaggregation technique. The continuous process model is transformed into a nonlinear programming (NLP) problem via discretization which uses an implicit integration method. The NLP problem is relaxed into a mixed integer linear programming (MILP) model. Iterations between solving MILP (lower bound) and using its solution as a starting point for a local nonlinear optimizer (which computes the upper bound) continue until the gap is closed (an l1-norm objective function is used). Controller performance is illustrated by several examples. Relative simplicity of the algorithm makes it possible to be implemented by a wide audience.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Process Control - Volume 52, April 2017, Pages 1-13
نویسندگان
, , ,