Title :
Model predictive engine control using support vector machine
Author :
Jun Lu;Weifeng Ma;Yongjun Han;Yuke Gao;Zhaoyuan Guo;Xin Li;Honglei Niu
Author_Institution :
The 705 Research Institute, China Shipbuilding Industry Corporation, Xi´an, Shaanxi Province, China
fDate :
6/1/2015 12:00:00 AM
Abstract :
This paper proposes a model predictive control strategy for the engine control. A data-driven modelling approach called support vector machine is used for modelling engine dynamics. More precisely, the engine model is developed by mapping the rotation speed as a function of fuel flow rate. Based on the SVM model, a model predictive controller is designed using Model Predictive Control Toolbox. The SVM model and the model predictive controller are implemented in the MATLAB/SIMULINK environment. Simulation results demonstrate the effectiveness of the model and the controller. The rotation speed is able to be maintained during abrupt changes in the load.
Keywords :
"Support vector machines","Engines","Fuels","Mathematical model","Load modeling","Predictive models","Predictive control"
Conference_Titel :
Cyber Technology in Automation, Control, and Intelligent Systems (CYBER), 2015 IEEE International Conference on
Print_ISBN :
978-1-4799-8728-3
DOI :
10.1109/CYBER.2015.7288179