Optimizing Vehicle Ride Comfort using GA-LQR Control in In-Wheel Suspension Systems

Controlled suspension systems, particularly active in-wheel suspension systems, are increasingly adopted in electric and autonomous vehicles due to their compact design and adaptability to various operating conditions. This study proposes the implementation of Linear Quadratic Regulator (LQR) controllers to improve vehicle smoothness and safety criteria. Genetic Algorithms (GA) are employed to optimize the weighting parameter values in the objective function in LQR controller, which allow them to adapt to the vehicle's condition. The simulation results demonstrate that the proposed controller model enhances system performance by up to 14% in comparison with conventional models. These findings suggest that the proposed system significantly enhances the feasibility of meeting user requirements in modern vehicle applications.