International Journal of Soft Computing
ISSN: OnlineISSN: Print 1816-9503
Abstract
In this study a comparison between two approaches in MBPC is made, the first one based on nonlinear programming NLP and the second based on a novel multi-agent controller for nonlinear models. Although, a nonlinear model predictive approach can achieve good performance and constraints fulfillment, its computational burden does not allow a real-time implementation and restricting the application to slow processes. In order to decrease the complexity of the controller, we propose a novel MPC scheme based on multi-agent controller approach. Simulation results show the effectiveness of the novel MPC scheme in reducing the computational burden, while achieving good results compared to NLMPC controller. Hence, the proposed approach has the potential to be applied to systems with faster time constants.
How to cite this article:
Ben Nasr Hichem and Faouzi M. Sahli . A Computational Time Requirement Comparison Between Two Approaches in MBPC.
DOI: https://doi.org/10.36478/ijscomp.2008.147.154
URL: https://www.makhillpublications.co/view-article/1816-9503/ijscomp.2008.147.154