Genetic algorithm inspired optimal integrated nonlinear control technique for an electric power steering system

Nguyen, Tuan Anh; Iqbal, Jamshed

Abstract

This paper introduces an optimal integrated control method for automotive steering systems called Backstepping Proportional Integral Derivative-Genetic Algorithm (BSPID-GA). The proposed algorithm combines Back Stepping Control (BSC) and Proportional Integral Derivative (PID) techniques with control coefficients optimally calculated by a genetic algorithm. The input to BSC is calibrated via an optimized PID controller instead of a direct signal. The novelty of the proposed control approach lies in utilizing the member algorithms' advantages to eliminate steady state errors and phase shift phenomena. Furthermore, the response speed and robustness of the system are significantly improved to resist the influence of external disturbances. The system's stability is evaluated according to the Lyapunov control function for nonlinear systems. A single-track dynamic model is set up to calculate the change in road reaction torque instead of assuming that this torque is a known input. Numerical computations and simulations are conducted in four specific cases corresponding to four types of driver torque. Results dictate that the output values (steering column and motor angle) closely track the reference values with the application of proposed control algorithm. The system steady state error is found to be nearly zero in the presence of external random nonlinear disturbances. The system stability and robustness are guaranteed in all the simulation scenarios considered, even with the variations in speed or driving torque. Moreover, the variation in actual assisted torque tends to follow the reference with minor errors. Compared with single control techniques (PID-GA or BSC), the performance of the integrated algorithm BSPID-GA is significantly higher.

Citation

Nguyen, T. A., & Iqbal, J. (2024). Genetic algorithm inspired optimal integrated nonlinear control technique for an electric power steering system. Journal of the Brazilian Society of Mechanical Sciences and Engineering, 46(11), Article 661. https://doi.org/10.1007/s40430-024-05255-5

• Journal Article Type: Article
• Acceptance Date: Oct 14, 2024
• Online Publication Date: Oct 18, 2024
• Publication Date: Nov 1, 2024
• Deposit Date: Oct 18, 2024
• Publicly Available Date: Oct 19, 2025
• Journal: Journal of the Brazilian Society of Mechanical Sciences and Engineering
• Print ISSN: 1678-5878
• Electronic ISSN: 1806-3691
• Publisher: Springer
• Peer Reviewed: Peer Reviewed
• Volume: 46
• Issue: 11
• Article Number: 661
• DOI: https://doi.org/10.1007/s40430-024-05255-5
• Keywords: Electric power steering (EPS); Genetic algorithm; Backstepping technique; Steering column angle; Steering motor angle
• Public URL: https://hull-repository.worktribe.com/output/4868385