One or more systems, methods and/or non-transitory, machine-readable mediums are described herein for controlling a suspension system. An active suspension control system can comprise a memory that stores executable components, and a processor, coupled to the memory, that executes or facilitates execution of the executable components comprising a dynamics model generator that generates a bioinspired dynamics model and determines nonlinear dynamics for nonlinear suppression of vibration of an active suspension system, a fuzzy disturbance observer component that determines a lumped disturbance to the active suspension system by employing fuzzy variables absent determination of exact physical parameters of the active suspension system, and a controller that applies respective outputs of the dynamics model generator and the fuzzy disturbance observer component, in combination with a non-cancelled state-coupling term, to control the active suspension system to thereby cause the nonlinear suppression of the vibration of the active suspension system.

A multi-degree-of-freedom active damping mechanism control method, system and a damping mechanism are provided. A skyhook active damping control algorithm is used for controlling an electric cylinder output force in a vertical damping direction, and an adaptive control algorithm with an adaptive rate is used for correcting a load moment of inertia in pitch and roll damping directions. At the same time, a predictive model is established according to a task space linearization equation near an equilibrium point, and states of the system at N future moments are predicted in advance at each moment to achieve optimal control under complex constraints and reduce the influence of system delay. At the same time, the three control methods may further improve the active damping effect of the damping device by combining road information obtained by a visual sensor in real time.