A Nonlinear Observer for Bioprocesses Using Lmi

Chiu, Nan-Chieh; Navarro, J.L.; Picó, Jesús

doi:10.3182/20070604-3-mx-2914.00067

Cited by 2 publications

(2 citation statements)

References 13 publications

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“…The filter has been utilized for estimating states and nonstationary disturbances; [20] provided a brief summary of some results concerning state and parameter estimation approaches in relation to the chemical and biochemical processes. In [21] the authors resorted to a linear matrix inequality (LMI) to determine the values of the gain matrix of the asymptotic and classic observer, those are applied to a linearized bioprocess model. In the same framework a nonlinear observer which actually utilized both LMI and Lyapunov function was studied in [22].…”

Section: Introductionmentioning

confidence: 99%

Unknown Inputs Nonlinear Observer for an Activated Sludge Process

Smida¹,

Ladhari²,

Said³

et al. 2018

Mathematical Problems in Engineering

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This paper deals with the jointly estimation problem of unknown inputs and nonmeasured states of one altering aerated activated sludge process (ASP). In order to provide accurate and economic concentration measures during aerobic and anoxic phases, a cascade high gain observer (HGO) approach is developed. Only two concentrations are available; the other process’s states are assumed unavailable. The observer converges asymptotically and it leads to a good estimation of the unavailable states which are the ammonia and substrate concentration, as well as a quite reconstruction of the unknown inputs, which are the influent ammonia and the influent substrate concentrations. To highlight the efficiency of the proposed HGO with this MIMO system’s dynamics, simulation results are validated with experimental data.

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Section: Introductionmentioning

confidence: 99%

Unknown Inputs Nonlinear Observer for an Activated Sludge Process

Smida¹,

Ladhari²,

Said³

et al. 2018

Mathematical Problems in Engineering

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show abstract

“…To solve this problem, various methods are proposed. We can quote, for example [32], [23], [14], [11], [34] and lately [6] and references therein. Reference [11] gives an excellent overview of available results on the state and parameter estimation approaches for chemical and biochemical processes.…”

Section: Introductionmentioning

confidence: 99%

A nonlinear observer design for an activated sludge wastewater treatment process

Boulkroune

Darouach

Zasadzinski

et al. 2009

Journal of Process Control

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This paper treats the problem of estimating simultaneously the state and the unknown inputs of a class of nonlinear discrete-time systems. An observer design method for nonlinear Lipschitz discrete-time systems is proposed. By assuming that the linear part of this class of systems is time-varying, the state estimation problem of nonlinear system is transformed into a state estimation problem for LPV system. The stability analysis is performed using a Lyapunov function that leads to the solvability of linear matrix inequalities (LMIs). Performances of the proposed observer are shown through the application to an activated sludge process model.

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A Nonlinear Observer for Bioprocesses Using Lmi

Cited by 2 publications

References 13 publications

Unknown Inputs Nonlinear Observer for an Activated Sludge Process

Unknown Inputs Nonlinear Observer for an Activated Sludge Process

A nonlinear observer design for an activated sludge wastewater treatment process

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