The paper proposes a fuzzy proportion integral differential (PID) control strategy based on road estimation to meet the different performance requirements of active suspension for comfort and safety under different road conditions in view of the uncertainty of vehicle suspension parameters and random road perturbations. First, flexible neural tree (FNT) is used to estimate the vertical disturbance of road within uncertain vehicle parameters in which the Fourier transform of the autocorrelation function is used to fit the road power spectrum density (PSD). In order to compensate for the delay and realize the real-time estimate of road conditions, an online fuzzy evaluation strategy for road condition is developed by integrating the fitted road PSD and the real-time suspension performance. After that, an adaptive fuzzy PID control strategy is developed based on the adaptive suspension control performance, which is supposed to realize the adaptive adjustment of control parameters for different road conditions. The simulation experimental results show that the online fuzzy evaluation strategy can effectively reflect the change in road condition, and the proposed adaptive fuzzy PID control strategy can work for adjusting the parameters adaptively, according to the changes in road conditions and therefore meet the control performance requirements under different road conditions.

The vehicle semi-active suspension system plays an important role in improving the driving safety and ride comfort by adjusting the coefficients of the damping and spring. The main contribution of this paper is the proposal of a PPO-based vibration control strategy for a vehicle semi-active suspension system, in which the designed reward function realizes the dynamic adjustment according to the road condition changes. More specifically, for the different suspension performances caused by different road conditions, the three performances of the suspension system, body acceleration, suspension deflection, and dynamic tire load, were taken as the state space of the PPO algorithm, and the reward value was set according to the numerical results of the passive suspension, so that the corresponding damping force was selected as the action space, and the weight matrix of the reward function was dynamically adjusted according to different road conditions, so that the agent could have a better improvement effect at different speeds and road conditions. In this paper, a quarter–car semi-active suspension model was analyzed and simulated, and numerical simulations were performed using stochastic road excitation for different classes of roads, vehicle models, and continuously changing road conditions. The simulation results showed that the body acceleration was reduced by 46.93% under the continuously changing road, which proved that the control strategy could effectively improve the performance of semi-active suspension by combining the dynamic changes of the road with the reward function.

In this article, the fault-tolerant control (FTC) problem of vehicle active suspension is concerned in the discrete-time domain, in which the road disturbances and faults in actuator and measurement are considered. The main contribution consists of proposing an active physically realizable fault-tolerant controller based on a reduced-order observer, which makes up an optimal vibration control component and an event-triggered FTC component. More specifically, by discussing a discrete vehicle active suspension subject to road disturbances generated from the output of a designed exosystem, the optimal vibration control component is derived from maximum principle to offset the inevitable vibrations. Meanwhile, based on the real-time system output of vehicle suspension rather than residual error, a reduced-order observer is proposed to cover the physically unrealizable problem for the designed optimal vibration control component. After that, an event-triggered FTC component and an event-triggered restructured system output are designed to compensate the faults in actuator and measurement, respectively. Finally, extensive experiments are conduced to the control performance of vehicle active suspension under the proposed controller, and confirm its effectiveness and superiority over other control schemes.