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Design and Implementation of Controller using MPC Toolbox

Omkar P. Dahale, Sharad P. Jadhav Published in Advanced Computing

IJAIS Proceedings on International Conference and workshop on Advanced Computing 2014
Year of Publication: 2014
© 2014 by IJAIS Journal
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  1. Omkar P Dahale and Sharad P Jadhav. Article: Design and Implementation of Controller using MPC Toolbox. IJAIS Proceedings on International Conference and workshop on Advanced Computing 2014 ICWAC 2014(1):11-17, June 2014. BibTeX

    	author = "Omkar P. Dahale and Sharad P. Jadhav",
    	title = "Article: Design and Implementation of Controller using MPC Toolbox",
    	journal = "IJAIS Proceedings on International Conference and workshop on Advanced Computing 2014",
    	year = 2014,
    	volume = "ICWAC 2014",
    	number = 1,
    	pages = "11-17",
    	month = "June",
    	note = "Published by Foundation of Computer Science, New York, USA"


Model Predictive Control Toolbox provides tools for systematically analyzing, designing, and tuning model predictive controllers. Design and Simulation of model predictive controllers using functions in MATLAB or blocks can be done in Simulink. The predictive model, control and prediction horizons, input and output constraints, and weights can also be modified. The toolbox enables us to diagnose issues that could lead to run-time failures and provides advice on changing weights and constraints to improve performance and robustness. By running different scenarios in linear and nonlinear simulations, the controller performance can be evaluated. Adjustments to controller performance can be made as it runs by tuning weights and varying constraints. For rapid prototyping and embedded system design, the toolbox supports C-code generation.


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Model Predictive Control (MPC), MPC Toolbox, Single Input Single Output (SISO), Single Input Multiple Outputs (SIMO), MATLAB, Simulink, MPC Controller.