(untitled) (OODBODHAN, 2024)
Active suspension systems are designed to improve vehicle ride comfort and handling stability by adapting to changing road conditions, surpassing the capabilities of traditional passive and semi-active systems. The article explores intelligent control approaches in active suspension systems, focusing on three main strategies: FLC (Fuzzy Logic Control), Fuzzy PID Control, and MPC (Model Predictive Control). FLC is highlighted for its capacity to manage uncertainties and nonlinear vehicle dynamics using rule-based decision-making. Fuzzy PID Control builds upon traditional PID control by incorporating fuzzy logic, enabling real-time adjustments and improved adaptability to road conditions. This approach improves performance in complex systems by optimizing control gains, enhancing stability and comfort. MPC is noted for its predictive capability, which optimizes control actions based on future states, making it highly effective in multi-variable and constraint-heavy applications, despite its computational demands. While FLC and Fuzzy PID are simpler and responsive, MPC provides the advantage of precision in complex, high-dimensional scenarios. Reducing MPC’s computational complexity for real-time use, enhancing adaptability through hybrid controls along with optimizing energy use alongside ride comfort and stability is the future in intelligent control of active suspension.