Title :
Nonlinear predictive control based on particle swarm optimization applied to pH neutralization reaction
Author_Institution :
Sch. of Autom. & Electr. Eng., Univ. of Sci. & Technol. Beijing, Beijing, China
fDate :
June 30 2012-July 2 2012
Abstract :
A nonlinear model predictive control (NMPC) strategy using particle swarm optimization (PSO) is presented in this paper. The PSO is improved by integrating chaotic local search (CLS) and roulette wheel mechanism (RWM). The new algorithm named RCPSO is adopted for solving the nonlinear optimization problem in NMPC. The NMPC based on RCPSO is implemented in the simulation of a neutralization reaction process for pH set-point tracking.
Keywords :
chemical engineering; chemical reactions; nonlinear control systems; nonlinear programming; pH; particle swarm optimisation; predictive control; search problems; CLS; NMPC strategy; PSO; RCPSO algorithm; RWM; chaotic local search; nonlinear model predictive control; nonlinear optimization problem; pH neutralization reaction process; pH set-point tracking; particle swarm optimization; roulette wheel mechanism; Mathematical model; Optimization; Particle swarm optimization; Prediction algorithms; Predictive control; Vectors; model predictive control; neutralization reaction; particle swarm optimizationt;
Conference_Titel :
System Science and Engineering (ICSSE), 2012 International Conference on
Conference_Location :
Dalian, Liaoning
Print_ISBN :
978-1-4673-0944-8
Electronic_ISBN :
978-1-4673-0943-1
DOI :
10.1109/ICSSE.2012.6257225
