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Academic Journal of Engineering and Technology Science, 2024, 7(2); doi: 10.25236/AJETS.2024.070204.

Weighting Coefficient Optimization of Active Suspension LQR Controller Based on Whale Optimization Algorithm


Shijie Yang

Corresponding Author:
Shijie Yang

School of Mechanical Engineering, Hunan University of Science and Technology, Xiangtan, China


In addressing the challenge of selecting weighting coefficients for performance indicators in the active suspension Linear Quadratic Regulator (LQR) control strategy, a Whale Optimization Algorithm (WOA) is proposed for optimizing the LQR controller's weighting coefficients. Leveraging the WOA's advantages in precision and convergence, the algorithm iteratively refines the values of the Q and R matrices in the LQR active control algorithm.A 1/4 vehicle model of the active suspension is established in the MATLAB/Simulink environment for simulation. By comparing the results with traditional LQR controllers, the designed WOA-optimized LQR controller is demonstrated to enhance the overall performance of the suspension system, significantly improving the vehicle's ride comfort and handling stability.


Active suspension, LQR controller, Whale Optimization Algorithm, Vehicle's ride comfort and handling stability

Cite This Paper

Shijie Yang. Weighting Coefficient Optimization of Active Suspension LQR Controller Based on Whale Optimization Algorithm. Academic Journal of Engineering and Technology Science (2024) Vol. 7, Issue 2: 20-27. https://doi.org/10.25236/AJETS.2024.070204.


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