A neurodynamic approach to bicriteria model predictive control of nonlinear affine systems based on a Goal Programming formulation

Zheng Yan, Jun Wang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

This paper presents a neurodynamic approach to bicriteria model predictive control (MPC) of nonlinear affine systems based on a goal programming formulation. Bicriteria MPC refers to finding optimal control inputs that minimizes two performance indexes corresponding to tracking errors and control efforts. The bicriteria MPC is formulated as the solution to a nonlinear optimization problem via goal programming technique and is solved by using a two-layer recurrent neural network. Simulation results are included to illustrate the effectiveness of the proposed approach.

Original languageEnglish
Title of host publication2012 International Joint Conference on Neural Networks, IJCNN 2012
DOIs
Publication statusPublished - 2012
Externally publishedYes
Event2012 Annual International Joint Conference on Neural Networks, IJCNN 2012, Part of the 2012 IEEE World Congress on Computational Intelligence, WCCI 2012 - Brisbane, QLD, Australia
Duration: 10 Jun 201215 Jun 2012

Publication series

NameProceedings of the International Joint Conference on Neural Networks

Conference

Conference2012 Annual International Joint Conference on Neural Networks, IJCNN 2012, Part of the 2012 IEEE World Congress on Computational Intelligence, WCCI 2012
Country/TerritoryAustralia
CityBrisbane, QLD
Period10/06/1215/06/12

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