In this paper, we introduced and explored the Laguerre and Kautz functions as an orthonormal functions based of model predictive control approach for automotive applications with particularly focuses on vehicle path following control and motor position control. The first implementation starting with the known trajectory, model predictive control based on linearized vehicle and tire model was used to follow the desired trajectory as close as possible, we performed a vehicle at middle speed maneuver on double lane change scenario. In the second application; predictive control is designed in order to track the desired motor position. We compared the predictive controllers designed based on Delta, Laguerre and Kautz functions for both applications in term of tracking error and position error performances. The result showed that the predictive control based on Kautz function gave a better tracking performance compared to Laguerre function and Delta function (conventional method). However, Laguerre function is easier and simpler in term of algorithm implementation than the other two functions. Moreover, for all functions based on predictive control; the simulation results demonstrated that orthonormal function can be implemented in predictive control approaches particularly to automotive application, thus, it is believe can be extended to other applications.
Weitere Kapitel dieses Buchs durch Wischen aufrufen
Bitte loggen Sie sich ein, um Zugang zu diesem Inhalt zu erhalten
Sie möchten Zugang zu diesem Inhalt erhalten? Dann informieren Sie sich jetzt über unsere Produkte:
- Exploting the Orthonormal Function Based on Model Predictive Control for Automotive Application
- Springer Berlin Heidelberg
Neuer Inhalt/© ITandMEDIA