2014
DOI: 10.1002/asjc.889
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Design of Full‐Order Observers for Systems with Unknown Inputs by Using the Eigenstructure Assignment

Abstract: In this paper a full-order observer is suggested in order to achieve finite-time reconstruction of the state vector for a class of linear systems with unknown inputs. The proposed design procedure is a combination of the approaches proposed by Lin & Wang [1] and Trinh & Ha [2]. The resulted observer has been improved, from the robustness point of view, by this paper's authors by using a novel and efficient method; it consists of adding three robustness terms which cancel the negative effect of the uncertaintie… Show more

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Cited by 19 publications
(16 citation statements)
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“…From aircraft dynamics' point of view, these represent unknown inputs; an observer for systems with unknown inputs may estimate these unknown inputs, but, more important, it must estimate the system states with very small errors [4]; therefore, in this paper, the unknown input vector V( ) has been randomly chosen. The decision and the activation functions have been chosen of the following forms: ( ) = ( ), 1 ( ( )) = 0.4(1 − tanh( ( ))), 2 ( ( )) = 1 − 1 ( ( )), where the input has the form = −̂, with the gain matrix determined by using the ALGLX optimal algorithm borrowed from [24]; can be also calculated by means of the pole placement technique or other methods.…”
Section: Numerical Simulation Setupmentioning
confidence: 99%
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“…From aircraft dynamics' point of view, these represent unknown inputs; an observer for systems with unknown inputs may estimate these unknown inputs, but, more important, it must estimate the system states with very small errors [4]; therefore, in this paper, the unknown input vector V( ) has been randomly chosen. The decision and the activation functions have been chosen of the following forms: ( ) = ( ), 1 ( ( )) = 0.4(1 − tanh( ( ))), 2 ( ( )) = 1 − 1 ( ( )), where the input has the form = −̂, with the gain matrix determined by using the ALGLX optimal algorithm borrowed from [24]; can be also calculated by means of the pole placement technique or other methods.…”
Section: Numerical Simulation Setupmentioning
confidence: 99%
“…The estimation of the states and unknown inputs (noises, measurement uncertainties, faults of sensors or actuators, etc.) for a physical system is needed in order to conceive a control strategy able to minimize the negative effects of the disturbances [4,5]. There are differences between the observers designed for linear or nonlinear systems, the design process being more difficult in the second case; to overcome this drawback, viable solutions can be the model order reduction [6,7] or the usage of the linearization method to obtain a linear system, because this technique (detailed in [8]) allows the transformation of any nonlinear system into the so-called multiple model-sum of linear models, each of them characterizing the system in a specific operating regime.…”
Section: Introductionmentioning
confidence: 99%
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“…Unknown-input observers (UIOs) have been the focus of research for several years [1][2][3][4]. This is due to the wide range of applications that already exist for this theory, like fault detection and observer-based control of electromechanical systems that are subjected to measurement noise, uncertainties, and disturbances [5][6][7][8].…”
Section: Introductionmentioning
confidence: 99%
“…This subject has recently been the focus of much research [1][2][3][4]. This subject has recently been the focus of much research [1][2][3][4].…”
Section: Introductionmentioning
confidence: 99%