Autors: Mitov, A. S., Kralev, J. K., Slavov, T. N., Angelov, I. I.
Title: Comparison between Model Predictive (MPC) and Model Reference Adaptive Controllers (MRAC) for Electrohydraulic Steering System Implemented as Real-Time Simulink® Program
Keywords: model predictive control, model referece adaptive control, e

Abstract: The purpose of the article is to investigate tracking performance of steering cylinder when controlled with two nonlinear controllers. The system under study is a laboratory electrohydraulic steering test rig. Two controls strategies are examined - model reference adaptive control (MRAC) and model predictive control (MPC). The MPC controller design is based on an identified model from experimental data in open-loop. The model is represented in state-space form and the future values of the state trajectory and output variables are used as optimization objective with respect to the future values of the control signal. Since this optimization procedure have to be performed every sampling interval and involve iterative calculation the implementation of MPC requires considerable computational resources. Hence, we have decided to develop a distributed computational platform, where the controller is executed in real-time as a Simulink model. The control and measurement signals are processed

References

    Issue

    IOP Conference Series: Materials Science and Engineering, 2020 International Scientific Conference on Aeronautics, Automotive and Railway Engineering and Technologies, BulTrans 2020, vol. 1002, pp. 1-12, 2020, Bulgaria, IOP Publishing Ltd, DOI:10.1088/1757-899X/1002/1/012034

    Copyright IOP Publishing Ltd

    Цитирания (Citation/s):
    1. Wang M., Chen J., Yang H., Wu X., Ye L., Path Tracking Method Based on Model Predictive Control and Genetic Algorithm for Autonomous Vehicle, Mathematical Problems in Engineering, Vol. 2022, ISSN:1024-123X, 2022 - 2022 - в издания, индексирани в Scopus или Web of Science

    Вид: публикация в национален форум с межд. уч., публикация в реферирано издание, индексирана в Scopus и Web of Science