64,456 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
Adaptive Control By Regulation-Triggered Batch Least-Squares Estimation of Non-Observable Parameters
The paper extends a recently proposed indirect, certainty-equivalence,
event-triggered adaptive control scheme to the case of non-observable
parameters. The extension is achieved by using a novel Batch Least-Squares
Identifier (BaLSI), which is activated at the times of the events. The BaLSI
guarantees the finite-time asymptotic constancy of the parameter estimates and
the fact that the trajectories of the closed-loop system follow the
trajectories of the nominal closed-loop system ("nominal" in the sense of the
asymptotic parameter estimate, not in the sense of the true unknown parameter).
Thus, if the nominal feedback guarantees global asymptotic stability and local
exponential stability, then unlike conventional adaptive control, the newly
proposed event-triggered adaptive scheme guarantees global asymptotic
regulation with a uniform exponential convergence rate. The developed adaptive
scheme is tested to a well-known control problem: the state regulation of the
wing-rock model. Comparisons with other adaptive schemes are provided for this
particular problem.Comment: 29 pages, 12 figure
Mathematical control of complex systems
Copyright © 2013 ZidongWang et al.This is an open access article distributed under the Creative Commons Attribution License,
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
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