1 research outputs found
Adaptive Finite-time Fuzzy Control of Nonlinear Active Suspension Systems With Input Delay
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,
e.g. gradient algorithm with e-modification or σ-modification.
In this framework, both the suspension and estimation errors
can achieve convergence in finite-time. 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