Note: This content is accessible to all versions of every browser. However, this browser does not seem to support current Web standards, preventing the display of our site's design details.


Model Predictive Control for Constrained Discrete-Time Systems: An Optimal Perturbation Analysis Approach


Reza Ghaemi

IfA Internal Seminar Series

Addressing computational issues in Model Predictive Control (MPC) is critical in making MPC applicable for systems with fast dynamics and limited computational resources. One MPC implementation strategy which alleviates computational demands is to approximate the MPC optimal control solution by a nominal solution (often pre-computed or computed off-line) and a perturbation solution. For systems without constraints, an optimal perturbation analysis has been well developed in the literature. The talk introduces a perturbation analysis method for discrete-time optimal control problems subject to a general class of inequality constraints, in order to approximate the optimal control solution. Moreover, an Integrated Perturbation Analysis and Sequential Quadratic Programming (IPA-SQP) algorithm which uses approximation of optimal solution according to perturbation analysis combined with SQP method will be presented. The proposed algorithm combines the complementary features of perturbation analysis and SQP in a single unified framework, thereby leading to improved computational efficiency.


Type of Publication:


File Download:

Request a copy of this publication.
(Uses JavaScript)
% No recipe for automatically generating a BibTex entry for (06)Talk
Permanent link