Abstract: An anti-carsickness active suspension robust genetic control method, which establishes a vehicle four-degree-of-freedom suspension model considering wheelbase preview, and the suspension designed by the disclosure meets the constraint conditions that the dynamic stroke does not exceed the maximum allowable stroke, the wheels keep good contact with the ground, the control force should be smaller than the maximum output control force of an actuator, and the like. Meanwhile, an objective function for preventing carsickness of a driver and passengers is established, a state output feedback control gain is solved based on a linear matrix inequality method, and a finite frequency domain robust control method optimized through a genetic algorithm is designed, so that optimal parameters of robust control are obtained. The control performance of the active suspension on road excitation in the motion sickness frequency interval is the best, and the riding comfort and the vehicle driving smoothness are improved.

Abstract: An anti-carsickness active suspension robust genetic control method, which establishes a vehicle four-degree-of-freedom suspension model considering wheelbase preview, and the suspension designed by the disclosure meets the constraint conditions that the dynamic stroke does not exceed the maximum allowable stroke, the wheels keep good contact with the ground, the control force should be smaller than the maximum output control force of an actuator, and the like. Meanwhile, an objective function for preventing carsickness of a driver and passengers is established, a state output feedback control gain is solved based on a linear matrix inequality method, and a finite frequency domain robust control method optimized through a genetic algorithm is designed, so that optimal parameters of robust control are obtained. The control performance of the active suspension on road excitation in the motion sickness frequency interval is the best, and the riding comfort and the vehicle driving smoothness are improved.

Abstract: The present disclosure discloses an active suspension control method under vehicle-mounted visual perception preview. It uses a binocular camera combined with multiple visual perception algorithms, and monitors in real time the road surface conditions ahead of the vehicle. By accurately capturing and analyzing the road surface information, based on robust control theory and Lyapunov theory, it designs a matching preview H? controller. The vehicle can effectively reduce bumps and vibrations by timely adjusting the suspension system, providing passengers with a more stable and smooth driving experience. The present disclosure uses a machine vision method to sense in advance the road surface information ahead, improving the time lag problem in the traditional suspension control method, thereby significantly improving the vehicle safety and ride comfort.