<abstract xmlns="http://www.w3.org/1999/xhtml"><p>The article presents a developed embedded system for control of electrohydraulic power steering based on multivariable uncertain plant model and advanced control techniques. The plant model is obtained by identification procedure via “black box” system identification and takes into account the deviations of the parameters that characterize the way that the control signal acts on the state of the model. Three types of controller are designed: Linear-Quadratic Gaussian (LQG) controller, H<sub>∞</sub> controller and μ-controller. The main result is a performed comparative analysis of time and frequency domain properties of control systems. The results show the better performance of systems based on µ-controllers. Also the robust stability and robust performance are investigated. All three systems achieved robust stability which guarantees their workability, but only the system with µ-controller has robust performance against prescribed uncertainties. The control algorithms are implemented in specialized 32-bit microcontroller. A number of real world experiments have been executed, which confirm the quality of the electrohydraulic power steering control system.</p></abstract>

The article presents a developed embedded system for control of electrohydraulic power steering based on multivariable uncertain plant model and advanced control techniques. The plant model is obtained by identification procedure via “black box” system identification and takes into account the deviations of the parameters that characterize the way that the control signal acts on the state of the model. Three types of controller are designed: Linear-Quadratic Gaussian (LQG) controller, H∞ controller and μ-controller. The main result is a performed comparative analysis of time and frequency domain properties of control systems. The results show the better performance of systems based on µ-controllers. Also the robust stability and robust performance are investigated. All three systems achieved robust stability which guarantees their workability, but only the system with µ-controller has robust performance against prescribed uncertainties. The control algorithms are implemented in specialized 32-bit microcontroller. A number of real world experiments have been executed, which confirm the quality of the electrohydraulic power steering control system.

Advanced Embedded Control of Electrohydraulic Power Steering System

Department. Hydroaerodynamics & Hydraulic Machines

Cybernetics and Information Technologies

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

{"article-title":"Advanced Embedded Control of Electrohydraulic Power Steering System"}

The article presents a developed embedded system for control of electrohydraulic power steering based on multivariable uncertain plant model and advanced...

Advanced Embedded Control of Electrohydraulic Power Steering System

Publicado en línea: 12 jun 2020

Páginas: 105 - 121

Recibido: 05 dic 2019

Aceptado: 16 mar 2020

DOI: https://doi.org/10.2478/cait-2020-0020

Palabras clave
Linear-Quadratic Gaussian (LQG) controller, Kalman filter, H controller, μ-controller, electrohydraulic steering system, embedded control

© 2020 Tsonyo Slavov et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Advanced Embedded Control of Electrohydraulic Power Steering System

Publicado en línea: 12 jun 2020

Páginas: 105 - 121

Recibido: 05 dic 2019

Aceptado: 16 mar 2020

DOI: https://doi.org/10.2478/cait-2020-0020

Palabras claveLinear-Quadratic Gaussian (LQG) controller, Kalman filter, H controller, μ-controller, electrohydraulic steering system, embedded control

© 2020 Tsonyo Slavov et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Palabras clave
Linear-Quadratic Gaussian (LQG) controller, Kalman filter, H controller, μ-controller, electrohydraulic steering system, embedded control