The extended Kalman filter as a noise modulator for continuous yeast cultures under monotonic, oscillating and chaotic conditions

Patnaik, Pratap R.

doi:10.1016/j.cej.2005.01.004

Cited by 14 publications

(12 citation statements)

References 27 publications

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“…EKF is observed to work for a range of these tuning parameters though convergence is not guaranteed [25,29].…”

Section: Soft Sensing Using Ekfmentioning

confidence: 94%

“…This technique does not guarantee optimal estimation as there is loss of information during the linearization process [26,27] and performs poorly when presented with constraints [28]. Nevertheless, EKF is known to provide convergent results for varying degrees of parameter changes in the model and also known as de facto filter [27,29,25]. The advantages of using EKF in the proposed strategy are: (i) provide an estimate of all the variables in the process at any time with noisy DO measurements and, (ii) fairly insensitive to mismatch between the true process and model.…”

Section: Introductionmentioning

confidence: 96%

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Model based predictive control for energy efficient biological nitrification process with minimal nitrous oxide production

Behera

Srinivasan

Chandran

et al. 2015

Chemical Engineering Journal

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“…EKF is observed to work for a range of these tuning parameters though convergence is not guaranteed [25,29].…”

Section: Soft Sensing Using Ekfmentioning

confidence: 94%

Section: Introductionmentioning

confidence: 96%

Model based predictive control for energy efficient biological nitrification process with minimal nitrous oxide production

Behera

Srinivasan

Chandran

et al. 2015

Chemical Engineering Journal

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“…Stochastic chaotic systems appear in many fields of science and engineering such as mechanical engineering [20], biology [21][22][23], chemistry [24], physics and laser science [25] and economics [26]. In most of these works, the stochastic chaos has been modeled by adding a bounded random process to some systems parameters or by applying a bounded random excitation to the input signal.…”

Section: Introductionmentioning

confidence: 99%

“…A general way to classify stochastic chaos is presented and is applied to population dynamic models in [23]. In [24] the relative intensity noise in a laser diode is considered as a result of the feedback-induced deterministic chaos and the intensity noise suppression is treated from the view point of chaos control. Controlling the Van der Pol oscillator under the influence of white noise in the regime below the Hopf bifurcation where the deterministic system has a stable fixed point and is not chaotic is investigated in [28].…”

Section: Introductionmentioning

confidence: 99%

Control of stochastic chaos using sliding mode method

Salarieh

Alasty

2009

Journal of Computational and Applied Mathematics

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a b s t r a c tStabilizing unstable periodic orbits of a deterministic chaotic system which is perturbed by a stochastic process is studied in this paper. The stochastic chaos is modeled by exciting a deterministic chaotic system with a white noise obtained from derivative of a Wiener process which eventually generates an Ito differential equation. It is also assumed that the chaotic system being studied has some model uncertainties which are not random. The sliding mode controller with some modifications is used for stochastic chaos suppression. It is shown that the system states converge to the desired orbit in such a way that the error covariance converges to an arbitrarily small bound around zero. As some case studies, the stabilization of 1-cycle and 2-cycle orbits of chaotic Duffing and Φ 6 Van der Pol systems is investigated by applying the proposed method to their corresponding stochastically perturbed systems. Simulation results show the effectiveness of the method and the accuracy of the statements proved in the paper.

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“…But the chaotic system may be affected by stochastic disturbances due to environmental noise [8,9]. Stochastic chaotic systems appear in many fields such as chemistry [10], physics and laser science [11], and economics [12]. So it is necessary to study such systems.…”

Section: Introductionmentioning

confidence: 99%

Passivity-Sliding Mode Control of Uncertain Chaotic Systems with Stochastic Disturbances

Liu

Wang

2014

Journal of Control Science and Engineering

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This paper is concerned with the stabilization problem of uncertain chaotic systems with stochastic disturbances. A novel sliding function is designed, and then a sliding mode controller is established such that the trajectory of the system converges to the sliding surface in a finite time. Using a virtual state feedback control technique, sufficient condition for the mean square asymptotic stability and passivity of sliding mode dynamics is derived via linear matrix inequality (LMI). Finally, a simulation example is presented to show the validity and advantage of the proposed method.

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The extended Kalman filter as a noise modulator for continuous yeast cultures under monotonic, oscillating and chaotic conditions

Cited by 14 publications

References 27 publications

Model based predictive control for energy efficient biological nitrification process with minimal nitrous oxide production

Model based predictive control for energy efficient biological nitrification process with minimal nitrous oxide production

Control of stochastic chaos using sliding mode method

Passivity-Sliding Mode Control of Uncertain Chaotic Systems with Stochastic Disturbances

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