Hybrid controllers based performance enhancement of off-road vehicle suspension system

Off-road vehicle drivers and passengers experience severe discomfort due to uneven road surfaces. In order to lessen this effect, the suspension system—which permits relative motion between the wheels and the vehicle frame—is essential. The suspension system guarantees road grip, handling stability, and efficient shock absorption in addition to improving ride comfort. In order to attain vibration stability under road disturbances like bumps, this study develops a small model of an off-road vehicle and designs appropriate controllers. With Integral Square Error (ISE), Integral Absolute Error (IAE), and Integral Time Absolute Error (ITAE) as objective functions, two hybrid control strategies are used: a Hybrid Ant Colony Optimization–Pattern Search (ACO-PS) algorithm-based PID controller and a Hybrid Model Predictive Control–Proportional Integral Derivative (MPC-PID) controller. Error indices, settling time, and peak overshoot are used to assess the system’s performance. In comparison to the Hybrid MPC-PID controller, the suggested Hybrid ACO-PS–based PID controller using ISE as the goal function provides a 3.3% faster settling time and 95% less vibration. In comparison to current controller designs, the suggested controller performs better overall.