Zoltán Szabó

55708578100

Publications - 6

Learning Nonlinear Models of Dynamic Systems

Zoltán Szabó J. Bokor

Publication Name: Sisy 2024 IEEE 22nd International Symposium on Intelligent Systems and Informatics Proceedings

Publication Date: 2024-01-01

Volume: Unknown

Issue: Unknown

Page Range: 11-15

Description:

Modeling dynamic systems is an important part in analysing and control of various systems arising either in health sciences or in the engineering word. Recent approaches to learn models from data are the so-called kernel-based methods and SVMs. There are strong relations to the theory of reproducing kernel Hilbert space (RKHS), to principal component analysis and canonic correlation analysis known previously from statistics. In recent form their use was extended from statistics to obtain models for dynamic systems. First we summarise the basics for the reproducing kernel based Hilbert space (RKHS) and the support vector machine (SVM) approaches. Following this it will be shown how some frequently used nonlinear models can be obtained by using these concepts. In the last part we discuss the structure estimation problem, i.e. how to determine the (least) number of features (observables) to describe the nonlinear system with a sparse representation.

Open Access: Yes

DOI: 10.1109/SISY62279.2024.10737570

Structure Selection and LPV Model Identification of a Car Steering Dynamics⁎

Gabor Rodonyi Zoltán Szabó Peter Koros Dániel Pup Alexandros Soumelidis J. Bokor

Publication Name: Unknown

Publication Date: 2018-01-01

Volume: 51

Issue: 15

Page Range: 1086-1091

Description:

A Linear Parameter-Varying (LPV), discrete-time black box model of an electric power assisted steering system of a passenger car is identified from open-loop step response measurement data. The goal is to provide a nominal model for control design and analysis that is able to describe the principal characteristics of the system in the whole region of steering angle and speed range of 3 to 30 km/h. Examining a set of experimental data by using classical linear time-invariant black box modeling and validation techniques, the structure of the LPV model is determined. The parameters of the model are identified based on minimizing a quadratic error criterion by nonlinear optimization algorithms.

Open Access: Yes

DOI: 10.1016/j.ifacol.2018.09.049

Robust reconfigurable control for in-wheel electric vehicles

Tímea Fülep András Mihály Zoltán Szabó Péter Gáspár Ferenc Szauter J. Bokor

Publication Name: IFAC Papersonline

Publication Date: 2015-09-01

Volume: 28

Issue: 21

Page Range: 36-41

Description:

The paper presents a fault tolerant reconfigurable control method for vehicles driven by four in-wheel electric motors and a steering system. The aim of the design is to realize robust velocity and road trajectory tracking even under challenging driving conditions or actuator failures. The vehicle is operated solely with the in-wheel motors, thus steering intervention is only applied in case of skidding or a failure of an electric motor. The reconfigurable control is realized based on Linear Parameter Varying (LPV) framework, using the specific characteristics of the in-wheel motors of fast and accurate torque control. The operation of the designed control system is demonstrated in a CarSim simulation environment.

Open Access: Yes

DOI: 10.1016/j.ifacol.2015.09.501

Hierarchical robust control for in-wheel motor vehicles

Tímea Fülep Péter Gáspár András Mihály Zoltán Szabó Ferenc Szauter J. Bokor

Publication Name: Proceedings of the Mini Conference on Vehicle System Dynamics Identification and Anomalies

Publication Date: 2014-01-01

Volume: 2014-January

Issue: Unknown

Page Range: 71-81

Description:

The paper proposes the design of an integrated vehicle control system for in-wheel electric vehicle, which is able to track road geometry with a predefined reference velocity. In the design the lateral and longitudinal dynamics are combined using the in-wheel motors and the steering system. The design methodology of the hierarchical control is proposed. The required control signals are calculated by applying high-level controllers, which are designed using a robust control method. For the control design the model is augmented with weighting functions specified by the performance demands. The actuators generating the necessary control signals in order to achieve the requirements for which low-level tracking controllers are designed.

Open Access: Yes

DOI: DOI not available

Robust reconfigurable control for in-wheel motor vehicles

Tímea Fülep Péter Gáspár András Mihály Zoltán Szabó Ferenc Szauter J. Bokor

Publication Name: 2014 IEEE International Electric Vehicle Conference Ievc 2014

Publication Date: 2014-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

The paper deals with reconfigurable control of in-wheel electric vehicles. Basically the vehicle is controlled alone by the four electric engines mounted in the wheels of the vehicle. The goal is to design a control system with velocity and trajectory tracking ability realized by separate torque generation of the in-wheel motors. In critical driving situations when the yaw moment cannot be established with the four in-wheel engine alone, the high-level controller reconfigures the actuator inputs, thus steering intervention helps to stabilize the vehicle. Moreover, a multi-layer supervisory architecture for integrated control systems is also proposed. The operation of the vehicle is illustrated through a CarSim simulation example.

Open Access: Yes

DOI: 10.1109/IEVC.2014.7056232

Integrated robust control design for in-wheel-motor vehicles

Tímea Fülep Zoltán Szabó Péter Gáspár Mihály András Ferenc Szauter J. Bokor

Publication Name: Fisita 2014 World Automotive Congress Proceedings

Publication Date: 2014-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

The paper proposes a multi-layer supervisory architecture for integrated control systems in road vehicles. The role of the supervisor is to coordinate active control components and provide priority among them. The supervisor has information about the current operational mode of the vehicle and it is able to make decisions about the necessary interventions into the vehicle components and guarantee the reconfigurable operation of the vehicle. The decisions of the supervisor are propagated to the lower layers through predefined interfaces encoded as suitable scheduling signals. The contribution of the paper is the application of the LPV methodology in a design case study in which an integrated control of four wheel independently-actuated electric vehicle with active steering system is developed.

Open Access: Yes

DOI: DOI not available