Acta Chimica Slovaca (ACS) publishes papers on fundamental and applied aspects of chemistry, biochemistry, chemical technology, chemical engineering and process control, biotechnology and food technology. Welcome are also topics which include chemical aspects of materials, physical chemistry and chemical physics, analytical chemistry, macromolecular chemistry and biomedical engineering.

Fast nonlinear model predictive control of a chemical reactor: a random shooting approach

Peter Bakaráč, Michal Kvasnica

Department of Information Engineering and Process Control Institute of Information Engineering, Automation, and Mathematics FCFT STU in Bratislava, Radlinského 9, 812 37 Bratislava, Slovakia

Abstract: This paper presents a fast way of implementing nonlinear model predictive control (NMPC) using the random shooting approach. Instead of calculating the optimal control sequence by solving the NMPC problem as a nonlinear programming (NLP) problem, which is time consuming, a sub-optimal, but feasible, sequence of control inputs is determined randomly. To minimize the induced sub-optimality, numerous random control sequences are selected and the one that yields the smallest cost is selected. By means of a motivating case study we demonstrate that the random shooting-based approach is superior, from a computational point of view, to state-of-the-art NLP solvers, and features a low level of sub-optimality. The case study involves a continuous stirred tank reactor where a fast multi-component chemical reaction takes place.

Keywords: nonlinear model predictive control, random shooting, continuous stirred tank reactor

Full paper in Portable Document Format: acs_0316.pdf

Acta Chimica Slovaca, Vol. 11, No. 2, 2018, pp. 175—181, DOI: 10.2478/acs-2018-0025