Machine learning

Convergence (economics)

Homotopy

Engineering

Artificial intelligence

Economics

Transient (computer programming)

Stability (learning theory)

Physics

Control engineering

Nonlinear system

Economic growth

Pure mathematics

CarSim

Mathematics

Fuzzy control system

Quantum mechanics

Operating system

Computer science

Suspension (topology)

Adaptive control

Actuator

Control (management)

Active suspension

Control theory (sociology)

Fuzzy logic

IEEE Transactions on Cybernetics

This paper presents a new adaptive fuzzy control scheme for active suspension systems subject to control input time delay and unknown nonlinear dynamics. First, a predictor-based compensation scheme is constructed to address the effect of input delay in the closed-loop system. Then, a fuzzy logic system (FLS) is employed as the function approximator to address the unknown nonlinearities. Finally, to enhance the transient suspension response, a novel parameter estimation error-based finite-time (FT) adaptive algorithm is developed to online update the unknown FLS weights, which differs from traditional estimation methods, for example, gradient algorithm with e -modification or σ -modification. In this framework, both the suspension and estimation errors can achieve convergence in FT. A Lyapunov-Krasovskii functional is constructed to prove the closed-loop system stability. Comparative simulation results based on a dynamic simulator built in a professional vehicle simulation software, Carsim, are provided to demonstrate the validity of the proposed control approach, and show its effectiveness to operate active suspension systems safely and reliably in various road conditions.

Adaptive Finite-Time Fuzzy Control of Nonlinear Active Suspension Systems With Input Delay