A tutorial overview of IPA-SQP approach for optimization of constrained nonlinear systems

Author

Hyeongjun Park ; Jing Sun ; Kolmanovsky, Ilya

Author_Institution

Dept. of Aerosp. Eng., Univ. of Michigan, Ann Arbor, MI, USA

fYear

2014

Firstpage

1735

Lastpage

1740

Abstract

This paper reviews the integrated perturbation analysis - sequential quadratic programming (IPA-SQP) approach. The IPA-SQP approach has been proposed to address computational challenges in nonlinear model predictive control (MPC) problems. This approach combines the complementary features of perturbation analysis and sequential quadratic programming in a unified framework. An overview of the IPA-SQP approach is provided, its methodological extension to adaptive MPC is discussed, and computational issues related to nonlinear MPC are discussed. Several successful applications of the IPA-SQP will also be highlighted. References to relevant literature are included.

Keywords

nonlinear control systems; predictive control; quadratic programming; IPA-SQP approach; MPC problems; adaptive MPC; constrained nonlinear systems; integrated perturbation analysis; nonlinear model predictive control; optimization; perturbation analysis; sequential quadratic programming; unified framework; Algorithm design and analysis; Equations; Heuristic algorithms; Optimal control; Optimization; Prediction algorithms; Real-time systems; Integrated perturbation analysis - sequential quadratic programming (IPA-SQP); Nonlinear model predictive control (NMPC); Numerical optimal control; Real-time optimization;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation (WCICA), 2014 11th World Congress on

Type

conf

DOI

10.1109/WCICA.2014.7052982

Filename

7052982