New Results of the Development and Application of Robust Observers

Söffker, Dirk

doi:10.1007/1-4020-4161-6_29

Cited by 3 publications

(1 citation statement)

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“…In , a robust PI‐observer is designed for stochastic linear systems and bounded convex uncertainty. In , the application of PI‐observer approach is to estimate both the original states and the bounded unknown inputs as extended states with high gains, without any information of the dynamics and bounds of the unknown inputs, which is also the function of the PI‐observer used here. Note that for stability reasons, the disturbances are assumed bounded, but the bounds themselves are not assumed.…”

Section: Introductionmentioning

confidence: 99%

Robust control approach for input–output linearizable nonlinear systems using high‐gain disturbance observer

Liu

Söffker

2012

Intl J Robust & Nonlinear

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SUMMARY This paper addresses a robust control approach for a class of input–output linearizable nonlinear systems with uncertainties and modeling errors considered as unknown inputs. As known, the exact feedback linearization method can be applied to control input–output linearizable nonlinear systems, if all the states are available and modeling errors are negligible. The mentioned two prerequisites denote important problems in the field of classical nonlinear control. The solution approach developed in this contribution is using disturbance rejection by applying feedback of the uncertainties and modeling errors estimated by a specific high‐gain disturbance observer as unknown inputs. At the same time, the nonmeasured states can be calculated from the estimation of the transformed system states. The feasibility and conditions for the application of the approach on mechanical systems are discussed. A nonlinear multi‐input multi‐output mechanical system is taken as a simulation example to illustrate the application. The results show the robustness of the control design and plausible estimations of full‐rank disturbances.Copyright © 2012 John Wiley & Sons, Ltd.

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Section: Introductionmentioning

confidence: 99%