Control engineering

Automotive engineering

Pure mathematics

Road surface

Mathematics

PID controller

Suspension (topology)

Adaptive control

Civil engineering

Engineering

Actuator

Artificial intelligence

Fuzzy control system

Control (management)

Ride quality

Active suspension

Computer science

Temperature control

Vehicle dynamics

Control theory (sociology)

Fuzzy logic

Homotopy

Electronics

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.

Adaptive Fuzzy PID Control Strategy for Vehicle Active Suspension Based on Road Evaluation