Application and Comparison of Optimal LQR Control Techniques for Engine Modeling

Volume 6 Issue 3 May - July 2018

Research Paper

Application and Comparison of Optimal LQR Control Techniques for Engine Modeling

Shashidhar S. Gokhale*, Yathisha L. **, Sudarshan S. Patil Kulkarni ***

* Ph.D. Scholar, Department of Electronics, Mysore University, Karnataka, India.

** Associate Professor, Department of Electronics and Communication Engineering, ATME College of Engineering, Mysore, Karnataka, India.

*** Professor, Department of Electronics and Communication Engineering, Sri Jayachamarajendra College of Engineering, Mysore, Karnataka, India.

Gokhale, S.S., Yathisha, L., & Kulkarni, S. S. P. (2018). Application and Comparison of Optimal LQR Control Techniques for Engine Modeling. i-manager’s Journal on Instrumentation and Control Engineering, 6(3), 36-43. https://doi.org/10.26634/jic.6.3.14684

Abstract

In the present scenario, the optimization of engine parameters is very much necessary for the smooth operation of automotive engines. This paper presents the three Optimal Linear Quadratic Control approaches for the state space engine model for the optimization of manifold pressure and engine speed state variables. The proposed three optimal controllers are Bryson, Bouderal, and Multistage Linear Quadratic Regulator (LQR) control techniques. The proposed controllers are applied and compared for the engine state space model using MATLAB/Simulink platform.