Design and application of multiple model predictive control in stroke control of hydrostatic transmission

The stroke control of a hydrostatic transmission (HST) has an important role for heavy-duty, on-highway, and off-road vehicles like agricultural and construction equipments along with mining and forestry vehicles to increase energy efficiency and power variability. The author proposes a multiple Model Predictive Controller (MPC) and multiple Model Reference Adaptive Control (MRAC) as a new control strategy for stroke control of HST, and compare their performances. The proposed controllers are based on a linear HST system mathematical model to track complex stroke reference trajectories of primary and secondary regulations under the realistic disturbances such as engine and load torques as a result of type of soil and field road conditions. The results of the Processor in the Loop simulations are encouraging in terms of the MPC having advantages over the MRAC and classical control strategies like being able to be designed for multi-input-multi-output systems, insensitive to external stochastic disturbances such as white noise as well as modeling errors and uncertainties to be implemented on an HST for real-time implementation.

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Publication Details

Journal
Advances in Mechanical Engineering
Published
2025-04-01
DOI
https://doi.org/10.1177/16878132251331720
Citations
1
Primary Topic
Iterative Learning Control Systems
Type
article
Field-Weighted Citation Impact
1.21
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article

Design and application of multiple model predictive control in stroke control of hydrostatic transmission

Hakan Ülker
1 citations
Advances in Mechanical Engineering
Iterative Learning Control Systems
1.21
article

Design and application of multiple model predictive control in stroke control of hydrostatic transmission

Hakan Ülker
article en
1 citations

Abstract

The stroke control of a hydrostatic transmission (HST) has an important role for heavy-duty, on-highway, and off-road vehicles like agricultural and construction equipments along with mining and forestry vehicles to increase energy efficiency and power variability. The author proposes a multiple Model Predictive Controller (MPC) and multiple Model Reference Adaptive Control (MRAC) as a new control strategy for stroke control of HST, and compare their performances. The proposed controllers are based on a linear HST system mathematical model to track complex stroke reference trajectories of primary and secondary regulations under the realistic disturbances such as engine and load torques as a result of type of soil and field road conditions. The results of the Processor in the Loop simulations are encouraging in terms of the MPC having advantages over the MRAC and classical control strategies like being able to be designed for multi-input-multi-output systems, insensitive to external stochastic disturbances such as white noise as well as modeling errors and uncertainties to be implemented on an HST for real-time implementation.

Advances in Mechanical EngineeringVol. 17(4)
Bursa Technical University (TR)
Openalex Percentile: Top 23%
Iterative Learning Control Systems
1.21
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