Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
697917 | Automatica | 2009 | 7 Pages |
Abstract
Computationally efficient algorithms are critical in making Model Predictive Control (MPC) applicable to broader classes of systems with fast dynamics and limited computational resources. In this paper, we propose an integrated formulation of Perturbation Analysis and Sequential Quadratic Programming (InPA-SQP) to address the constrained optimal control problems. The proposed algorithm combines the complementary features of perturbation analysis and SQP in a single unified framework, thereby leading to improved computational efficiency and convergence property. A numerical example is reported to illustrate the proposed method and its computational effectiveness.
Related Topics
Physical Sciences and Engineering
Engineering
Control and Systems Engineering
Authors
Reza Ghaemi, Jing Sun, Ilya V. Kolmanovsky,