Journals / International Journal of Automotive Science and Technology / 2026 / Volume: 10 Issue: 3

Robustness Assessment of Feedback Self-Tuning Controller for Steering Feel in Steer-by-Wire Systems through Numerical Simulation Approach

Muhamad Asri Azizul(Universiti Tun Hussein Onn Malaysia)0000-0003-4358-5558
Fauzi Bin Ahmad(Universiti Teknikal Malaysia Melaka)0000-0002-0790-7348
Juffrizal Karjanto(Universiti Teknikal Malaysia Melaka)0000-0002-9309-7141
Mohamed Hafiz Md Isa(Universiti Teknikal Malaysia Melaka)0000-0002-0065-9767
Haziq Hamdi(Universiti Teknikal Malaysia Melaka)0009-0002-3460-7399
Pages
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Publication Date
2026-09-08
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Additionally, the results indicated that the proposed controller was capable of replicating the steering feel of a conventional steering system with a mean absolute error (MAE) of less than 1.90.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:This study introduces a novel and highly applicable torque tracking algorithm as a controller to develop a realistic steering feel in a front steer-by-wire (SbW) architecture.
📊
Key Findings & Data:The objective of this study was to propose a self-tuning PI-based controller using a gain scheduling method to mimic the torque generated by a rack and pinion system through the torque produced by a DC motor.
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Conclusion & Impact:Additionally, the results indicated that the proposed controller was capable of replicating the steering feel of a conventional steering system with a mean absolute error (MAE) of less than 1.90.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Torque Tracking Control · Steer-by-Wire · Steering Feel

Abstract

This study introduces a novel and highly applicable torque tracking algorithm as a controller to develop a realistic steering feel in a front steer-by-wire (SbW) architecture. The objective of this study was to propose a self-tuning PI-based controller using a gain scheduling method to mimic the torque generated by a rack and pinion system through the torque produced by a DC motor. To provide the foundation for the torque tracking control strategy, a full car model with 14 degrees of freedom was developed to assess the efficacy of the proposed control scheme in generating the steering feel. Based on the Newton’s second law, the SbW model was developed and verified using a step input signal in two extreme conditions. The performance of the proposed controller and its robustness were validated through two vehicle dynamic tests based on ISO standard, the Double Lane Change (DLC) and Slalom (SL) tests under varying vehicle speeds and extreme maneuvers. This robustness assessment demonstrates that the gain-scheduling proportional-integral (GS-PI) controller performs significantly well in tracking the desired steering wheel torque, compared to the results from the CarSim software, which served as a benchmark. Additionally, the results indicated that the proposed controller was capable of replicating the steering feel of a conventional steering system with a mean absolute error (MAE) of less than 1.90. This study prepares a platform for practical applications in developing realistic steering feel in future SbW systems. Furthermore, the control proposed in this study provides a practical control system approach suitable for hardware implementation.

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Cite This Article

Azizul, M. A., Ahmad, F. B., Karjanto, J., Isa, M. H. M., Hamdi, H. (2026). Robustness Assessment of Feedback Self-Tuning Controller for Steering Feel in Steer-by-Wire Systems through Numerical Simulation Approach. International Journal of Automotive Science and Technology, Volume: 10 Issue: 3. https://doi.org/10.30939/ijastech..1871830

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References (42)

  1. Lu Y, Zhong J, Khoshnevisan L, Sun C, Khajepour A. A review on vehicle steer-by-wire control systems. Veh Syst Dyn. 2025:1-33. https://doi.org/10.1080/00423114.2025.2589913.
  2. Mortazavizadeh SA, Ghaderi A, Ebrahimi M, Hajian M. Recent developments in the vehicle steer-by-wire system. IEEE Trans Transp Electrif. 2020;6(3):1226-1235. https://doi.org/10.1109/TTE.2020.3004694.
  3. Bajçinca N, Cortesão R, Hauschild M. Robust control for steer-by-wire vehicles. Auton Robot. 2005;19(2):193-214. https://doi.org/10.1007/s10514-005-0608-2.
  4. Kuyu YÇ. Trajectory tracking control using evolutionary approaches for autonomous driving. Int J Automot Sci Technol. 2024;8(1):110-117. https://doi.org/10.30939/ijastech.1354082.
  5. Demir U, Kamış Kocabıçak Z. Investigation on different driving cycle and scenarios considering the autonomous electric vehicles. Int J Automot Sci Technol. 2022;6(4):364-378. https://doi.org/10.30939/ijastech.1178321.
  6. Perozzi G, Rath JJ, Sentouh C, Floris J, Popieul JC. Lateral shared sliding mode control for lane keeping assist system in steer-by-wire vehicles: theory and experiments. IEEE Trans Intell Veh. 2023;8(4):3073-3082. https://doi.org/10.1109/TIV.2021.3097352.
  7. Irmer M, Degen R, Nüßgen A, Thomas K, Henrichfreise H, Ruschitzka M. Development and analysis of a detail model for steer-by-wire systems. IEEE Access. 2023;11:7229-7236. https://doi.org/10.1109/ACCESS.2023.3238107.
  8. Yu L, Hu Z, Zhang H, Wu X, Huang H, Liu X. Road feel simulation strategy for steer-by-wire system in electric vehicles based on an improved nonlinear second-order sliding mode observer. World Electr Veh J. 2025;16(6):294. https://doi.org/10.3390/wevj16060294.
  9. Xiao P, Fang Z, Jin K, Zhang R, Yang A. Study of the road feel model of a steer-by-wire system based on an improved dung beetle optimization algorithm. Electr Eng. 2025;107(6):8129-8140. https://doi.org/10.1007/s00202-025-02964-5.
  10. Beal CE, Brennan S. Modeling and friction estimation for automotive steering torque at very low speeds. Veh Syst Dyn. 2021;59(3):458-484. https://doi.org/10.1080/00423114.2019.1708416.
  11. Su C, Li H, Qiao B, Wu X. Personalized steering feel design for steer-by-wire systems based on the rack force estimation. Int J Automot Technol. 2023;24(4):1151-1161. https://doi.org/10.1007/s12239-023-0094-6.
  12. Alex A, Saleem A. A Lyapunov-based dual controller approach with PSO tuning for steer-by-wire systems with artificial steering feel. IEEE Access. 2024;12:188976-188992. https://doi.org/10.1109/ACCESS.2024.3516207.
  13. Zhao R, Deng W, Ren B, Ding J. Modeling on steering feedback torque based on data-driven method. IEEE/ASME Trans Mechatron. 2022;27(5):2775-2785. https://doi.org/10.1109/TMECH.2021.3119751.
  14. Woo S, Heo C, Jeong MO, Lee JM. Integral analysis of a vehicle and electric power steering logic for improving steering feel performance. Appl Sci. 2023;13(20):11598. https://doi.org/10.3390/app132011598.
  15. Lee J, Chang S, Kim K, Jang B, Lee D, Lee B, et al. Steering wheel torque control of steer-by-wire system for steering feel. SAE Technical Paper 2017-01-1567. SAE International; 2017. https://doi.org/10.4271/2017-01-1567.
  16. Zhou H, Pang A, Yang J, He Z. Structured H∞ control of an electric power steering system. Complexity. 2020;2020:9371327. https://doi.org/10.1155/2020/9371327.
  17. Heinrich F, Kaste J, Kabil SG, Sanne M, Küçükay F, Henze R, et al. Methods for modeling the steering wheel torque of a steer-by-wire vehicle. Automot Engine Technol. 2022;7(1-2):53-64. https://doi.org/10.1007/s41104-021-00093-2.
  18. Cheon D, Nam K, Oh S. Design and robust control of a precise torque controllable steering module for steer-by-wire systems. IEEE Trans Ind Electron. 2022;69(12):13245-13254. https://doi.org/10.1109/TIE.2021.3139195.
  19. Hwang H, Choi H, Nam K. Practical synchronous steering angle control of a dual-motor driving steer-by-wire system. IEEE Access. 2019;7:133100-133110. https://doi.org/10.1109/ACCESS.2019.2938803.
  20. Husain SS, Kadhim MQ, Al-Obaidi ASM, Hasan AF, Humaidi AJ, Al Husaeni DN. Design of robust control for vehicle steer-by-wire system. Indones J Sci Technol. 2023;8(2):197-216. https://doi.org/10.17509/ijost.v8i2.54794.
  21. Cruz-Bernal A. Meta-heuristic optimization techniques and its applications in robotics. In: Del Ser Lorente J, editor. Recent advances on meta-heuristics and their application to real scenarios. Rijeka: InTech; 2013. https://doi.org/10.5772/54460.
  22. Şen MA, Kalyoncu M. Optimal tuning of PID controller using grey wolf optimizer algorithm for quadruped robot. Balkan J Electr Comput Eng. 2018;6(1):29-35. https://doi.org/10.17694/bajece.401992.
  23. Sandoval D, Soto I, Adasme P. Control of direct current motor using ant colony optimization. In: 2015 Chilean Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON); 2015 Oct 28-30; Santiago, Chile. IEEE; 2015. p. 79-82. https://doi.org/10.1109/CHILECON.2015.7400356.
  24. Azizul MA, Ahmad F, Karjanto J, Md Isa MH, Mohamed N. Adaptive PI-based control for steering torque feedback in steer-by-wire systems: a physical modeling approach. Int J Automot Mech Eng. 2025;22(3):12748-12777. https://doi.org/10.15282/ijame.22.3.2025.16.0973.
  25. Azizul MA, Ahmad F, Karjanto J, Che Hasan MH, Sulaiman S. Modelling, simulation and testing of steer-by-wire system with variable steering ratio control strategy in 14-DOF full vehicle model. Int J Automot Mech Eng. 2024;21(4):11784-11808. https://doi.org/10.15282/ijame.21.4.2024.5.0906.
  26. Luu DL, Quang Trung N, Thien To N. Enhancement of ride comfort in active quarter-car suspension systems using model predictive control. Int J Automot Sci Technol. 2025;9(4):527-535. https://doi.org/10.30939/ijastech.1701968.
  27. Çelik İ, Arslan TA, Aysal FE, Bayrakçeken H, Oğuz Y. Comparison of control methods for half-car active suspension system. Int J Automot Sci Technol. 2024;8(4):439-450. https://doi.org/10.30939/ijastech.1578123.
  28. Eroğlu M, Koç MA, Kozan R, Esen İ. Comparative analysis of full car model with driver using PID and LQR controllers. Int J Automot Sci Technol. 2022;6(2):178-188. https://doi.org/10.30939/ijastech.1076443.
  29. Hamdi MH, Ahmad F, Che Hasan MH, Harun MH, Aparow VR. Model reference adaptive control of an independent steer-by-wire system: a simulation using a 14-degree-of-freedom vehicle model. Int J Automot Mech Eng. 2024;21(4):11723-11743. https://doi.org/10.15282/ijame.21.4.2024.1.0904.
  30. Azizul MA, Ahmad F, Karjanto J, Che Hasan MH, Razak MSA, Hamdi MH. Development, modelling and validation of full vehicle model integrated with Magic Formula tire model. In: Raharjo WP, Imaduddin F, Smaradhana DF, editors. Proceedings of the 10th International Conference and Exhibition on Sustainable Energy and Advanced Materials (ICE-SEAM 2024). Lecture Notes in Mechanical Engineering. Singapore: Springer; 2025. p. 319-336. https://doi.org/10.1007/978-981-96-5063-7_26.
  31. Theodoro FRF, Reis MLCC, Souto CDA, de Barros E. Measurement uncertainty of a pressure sensor submitted to a step input. Measurement. 2016;88:238-247. https://doi.org/10.1016/j.measurement.2016.03.043.
  32. Mao X, Xiang C, Wu D, Wu Y, Lai Q. Effect analysis of step input smoothing optimization on hydraulic excitation suppression of position servo system. J Phys Conf Ser. 2022;2396(1):012028. https://doi.org/10.1088/1742-6596/2396/1/012028.
  33. Han Y, He L, Wang X, Zong C. Research on torque ratio based on the steering wheel torque characteristic for steer-by-wire system. J Appl Math. 2014;2014:929164. https://doi.org/10.1155/2014/929164.
  34. Fankem S, Müller S. A new model to compute the desired steering torque for steer-by-wire vehicles and driving simulators. Veh Syst Dyn. 2014;52(Suppl 1):251-271. https://doi.org/10.1080/00423114.2014.896469.
  35. He L, Li F, Guo C, Gao B, Lu J, Shi Q. An adaptive PI controller by particle swarm optimization for angle tracking of steer-by-wire. IEEE/ASME Trans Mechatron. 2022;27(5):3830-3840. https://doi.org/10.1109/TMECH.2021.3137848.
  36. Choi H, Choi S. Design of the steering feedback controller of a steer-by-wire system using admittance model. Int J Automot Technol. 2024;25(3):565-574. https://doi.org/10.1007/s12239-024-00055-1.
  37. Zhang H, Jiang W, Zhao W, Li Y. Tracking and fault-tolerant controller design for uncertain steer-by-wire systems using model predictive control. Chin J Mech Eng. 2024;37(1):141. https://doi.org/10.1186/s10033-024-01110-9.
  38. Kuyu YÇ. Trajectory tracking control using evolutionary approaches for autonomous driving. Int J Automot Sci Technol. 2024;8(1):110-117. https://doi.org/10.30939/ijastech.1354082.
  39. Demir U, Kamış Kocabıçak Z. Investigation on different driving cycle and scenarios considering the autonomous electric vehicles. Int J Automot Sci Technol. 2022;6(4):364-378. https://doi.org/10.30939/ijastech.1178321.
  40. Luu DL, Quang Trung N, Thien To N. Enhancement of ride comfort in active quarter-car suspension systems using model predictive control. Int J Automot Sci Technol. 2025;9(4):527-535. https://doi.org/10.30939/ijastech.1701968.
  41. Çelik İ, Arslan TA, Aysal FE, Bayrakçeken H, Oğuz Y. Comparison of control methods for half-car active suspension system. Int J Automot Sci Technol. 2024;8(4):439-450. https://doi.org/10.30939/ijastech.1578123.
  42. Eroğlu M, Koç MA, Kozan R, Esen İ. Comparative analysis of full car model with driver using PID and LQR controllers. Int J Automot Sci Technol. 2022;6(2):178-188. https://doi.org/10.30939/ijastech.1076443.