Synergistic Integration of LQR Control and PSO Optimization for Advanced Active Suspension Systems Utilizing Electro-Hydraulic Actuators and Electro-Servo Valves

  • Trong Tu Do
Keywords: active suspension system, electro-hydraulic actuator, vehicle comfort, road holding, vehicle vibration, particle swarm optimization, linear quadratic regulator

Abstract

This paper investigates the design and optimization of Linear Quadratic Regulator (LQR) controllers for vehicle active suspension systems, incorporating an electro-hydraulic actuator with an electro-servo valve. To enhance both vehicle comfort and road-holding stability, we employ Particle Swarm Optimization (PSO) to optimize the LQR controller parameters. The active suspension system model includes the dynamics of the electro-hydraulic actuator and the electro-servo valve, providing a realistic and practical framework for heavy vehicles. By leveraging PSO, the LQR controller parameters are fine-tuned to minimize a cost function that integrates both comfort and stability up to 76.91%. The results demonstrate substantial improvements in ride comfort and road-holding stability compared to traditional passive suspension systems. This research remarks the fundamentals of the experimental validation and further refinement of these control algorithms to adapt to various driving conditions and vehicle models, ultimately aiming to transition these optimized controllers from theoretical frameworks to practical, real-world applications.

Downloads

Download data is not yet available.

References

A. Azizi and H. Mobki, Applied Mechatronics: Designing a Sliding Mode Controller for Active Suspension System, Complexity, vol. 2021, no. 1, 2021.

M. A. Koç, A new expert system for active vibration control (AVC) for high-speed train moving on a flexible structure and PID optimization using MOGA and NSGA-II algorithms, Journal of the Brazilian Society of Mechanical Sciences and Engineering, vol. 44, no. 4, p. 151, 2022.

D. T. Tu, Active in-Wheel Suspension Performance Analysis Using Linear Quadratic Controllers, in 2023 International Conference on Control, Robotics and Informatics (ICCRI), IEEE, pp. 1–6, May 2023.

R. Pečeliūnas, Influence of Semi-Active Suspension Characteristics on the Driving Comfort, Advances in Science and Technology Research Journal, vol. 14, no. 1, pp. 18–25, 2020.

N. Alshabatat and T. Shaqarin, Impact of Using an Inerter on the Performance of Vehicle Active Suspension, Advances in Science and Technology Research Journal, vol. 16, no. 3, pp. 331–339, 2022.

A. A. Ferhath and Kamalakkannan Kasi, A Review on Various Control Strategies and Algorithms in Vehicle Suspension Systems, International Journal of Automotive and Mechanical Engineering, vol. 20, no. 3, pp. 10720–10735, 2023.

T. Samakwong and W. Assawinchaichote, PID Controller Design for Electro-hydraulic Servo Valve System with Genetic Algorithm, Procedia Computer Science, vol. 86, pp. 91–94, 2016.

J. Mi, J. Yu, and G. Huang, Direct-Drive Electro-Hydraulic Servo Valve Performance Characteristics Prediction Based on Big Data and Neural Networks, Sensors, vol. 23, no. 16, p. 7211, 2023.

S. Kumar, A. Medhavi, and R. Kumar, Optimization of Nonlinear Passive Suspension System to Minimize Road Damage for Heavy Goods Vehicle, The International Journal of Acoustics and Vibration, vol. 26, no. 1, pp. 56–63, 2021.

W. AL-ASHTARI, Fuzzy logic control of active suspension system equipped with a hydraulic actuator, International Journal of Applied Mechanics and Engineering, vol. 28, no. 3, pp. 13–27, 2023.

S. Liu, R. Hao, D. Zhao, and Z. Tian, Adaptive Dynamic Surface Control for Active Suspension With Electro-Hydraulic Actuator Parameter Uncertainty and External Disturbance, IEEE Access, vol. 8, pp. 156645–156653, 2020.

D. Rodriguez-Guevara, A. Favela-Contreras, F. Beltran-Carbajal, C. Sotelo, and D. Sotelo, An MPC-LQR-LPV Controller with Quadratic Stability Conditions for a Nonlinear Half-Car Active Suspension System with Electro-Hydraulic Actuators, Machines, vol. 10, no. 2, p. 137, 2022.

J. Gonera, Influence of the Size and Distribution of Load on the Damping Coefficient of Shock Absorbers in Passenger Vehicles, Advances in Science and Technology Research Journal, vol. 14, no. 4, pp. 185–194, 2020.

S. Manna et al., Ant Colony Optimization Tuned Closed-Loop Optimal Control Intended for Vehicle Active Suspension System, IEEE Access, vol. 10, pp. 53735–53745, 2022.

S. M. H. Baygi and A. Karsaz, A hybrid optimal PID-LQR control of structural system: A case study of salp swarm optimization, in 2018 3rd Conference on Swarm Intelligence and Evolutionary Computation (CSIEC), IEEE, pp. 1–6, Mar. 2018.

S. Das, I. Pan, and S. Das, Multi-objective LQR with optimum weight selection to design FOPID controllers for delayed fractional order processes, ISA Transactions, vol. 58, pp. 35–49, 2015.

M. Nagarkar, Y. Bhalerao, G. V. Patil, and R. Z. Patil, Multi-Objective Optimization of Nonlinear Quarter Car Suspension System – PID and LQR Control, Procedia Manufacturing, vol. 20, pp. 420–427, 2018.

M. Jain, V. Saihjpal, N. Singh, and S. B. Singh, An Overview of Variants and Advancements of PSO Algorithm, Applied Sciences, vol. 12, no. 17, p. 8392, 2022.

F. Marini and B. Walczak, Particle swarm optimization (PSO). A tutorial, Chemometrics and Intelligent Laboratory Systems, vol. 149, pp. 153–165, 2015.

R. R. Das, V. K. Elumalai, R. Ganapathy Subramanian, and K. V. Ashok Kumar, Adaptive predator–prey optimization for tuning of infinite horizon LQR applied to vehicle suspension system, Applied Soft Computing Journal, vol. 72, pp. 518–526, 2018.

L. Vanneschi and S. Silva, Particle Swarm Optimization, in Natural Computing Series, 2023, pp. 105–111, 2023.

Y.-P. Zhou, L.-J. Tang, J. Jiao, D.-D. Song, J.-H. Jiang, and R.-Q. Yu, Modified Particle Swarm Optimization Algorithm for Adaptively Configuring Globally Optimal Classification and Regression Trees, Journal of Chemical Information and Modeling, vol. 49, no. 5, pp. 1144–1153, 2009.

F. Li et al., Development of a Control System for Double-Pendulum Active Spray Boom Suspension Based on PSO and Fuzzy PID, Agriculture, vol. 13, no. 9, p. 1660, 2023.

Lei Tang, Ningsu Luo Ren, and S. Funkhouser, Semi-active Suspension Control with PSO Tuned LQR Controller Based on MR Damper, International Journal of Automotive and Mechanical Engineering, vol. 20, no. 2, pp. 10512–10522, 2023.

M. Li, J. Xu, Z. Wang, and S. Liu, Optimization of the Semi-Active-Suspension Control of BP Neural Network PID Based on the Sparrow Search Algorithm, Sensors, vol. 24, no. 6, p. 1757, 2024.

T. Akgul and A. Unluturk, Comparison of PSO-LQR and PSO-PID Controller Performances on a Real Quarter Vehicle Suspension, in 2023 Innovations in Intelligent Systems and Applications Conference (ASYU), IEEE, pp. 1–6, Oct. 2023.

Published
2025-06-16
How to Cite
Trong Tu. (2025). Synergistic Integration of LQR Control and PSO Optimization for Advanced Active Suspension Systems Utilizing Electro-Hydraulic Actuators and Electro-Servo Valves. EMITTER International Journal of Engineering Technology, 13(1), 56-72. https://doi.org/10.24003/emitter.v13i1.892
Section
Articles