Unscented Kalman filter based nonlinear model predictive control of a LDPE autoclave reactor

Jacob, Noel C.; Dhib, Ramdhane

doi:10.1016/j.jprocont.2011.06.013

Cited by 35 publications

(26 citation statements)

References 34 publications

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“…However, the performance of the NMPC algorithm appears to be only somewhat superior to the Kalman filter based LMPC formulation for the stabilization of the reactor system about a given equilibrium point. These results differ qualitatively from a previous study on single-zone LDPE autoclave reactors [48], where the UKF based NMPC algorithm appeared to provide a significant enhancement in closed-loop performance with respect to LMPC and PID controllers. The results demonstrate also that the closedloop performance of NMPC algorithm withstands quite well the effects of structural and parametric mismatch between the plant and controller models.…”

Section: Discussioncontrasting

confidence: 99%

Nonlinear MPC of a multi-zone multi-feed LDPE autoclave reactor

Jacob

Dhib

2012

Journal of Industrial and Engineering Chemistry

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Section: Discussioncontrasting

confidence: 99%

Nonlinear MPC of a multi-zone multi-feed LDPE autoclave reactor

Jacob

Dhib

2012

Journal of Industrial and Engineering Chemistry

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“…(16) in UGSF). Thus the posterior moments should be modified such that the point estimate will be bound to the state constraints.…”

Section: Update Stepmentioning

confidence: 99%

“…On the other hand, the Unscented Transformation (UT) [1] based approaches use a limited but deterministic choice of 2n + 1 samples (n -dimension of state vector), known as sigma points, to capture moments of the non-Gaussian densities. This parsimonious number of sigma points is the primary reason for the popularity of UT based approaches [16], [17], [5]. The UT based approaches may be further classified into three broad classes: (i) UKF [1]: assumes all underlying densities as Gaussian and uses 2n + 1 sigma points to represent the initial posterior and the nonlinearly transformed prior.…”

Section: Introductionmentioning

confidence: 99%

Projection based constrained nonlinear state estimation using Gaussian sum filters

Kottakki

Bhushan

Bhartiya

2016

2016 Indian Control Conference (ICC)

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Constraint handling is an integral part of any practical state estimation procedure. Most current approaches to constrained state estimation ensure that the point estimate is feasible with respect to the constraints and are based on popular unconstrained approaches such as sampling based approaches such as Unscented Kalman Filter (UKF) [1], which use deterministically chosen set of sigma points. However, UKF is based on an implicit assumption that the conditional state densities at various steps are Gaussian. In a recent work [2], a new filter termed as Unscented Gaussian Sum Filter (UGSF) was proposed that represents the prior density as a Gaussian sum. It was shown, using simulation studies, that the UGSF outperforms UKF thereby demonstrating the advantage of using a non-Gaussian prior. In this work, we propose to extend UGSF to constrained UGSF by incorporation of constraints on the states in the estimation process. In particular, we propose to use Interval Constrained Unscented Transformation (ICUT) [3] and projection algorithm [4] with the UGSF framework. Implementation on the three state isothermal batch reactor case study [5] shows that the proposed constrained UGSF using the projection method outperforms constrained UKF while maintaining the computation effort similar to the constrained UKF version.

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“…More recently, Kehinde et al conducted an interesting review on the current state‐of‐art of polyolefins production in high‐pressure processes. Also, several studies were done on process optimization and control . In particular, Embiruçu et al conducted an interesting survey on steady‐state optimization and advanced process control strategies of polymer reactors; whereas Jacob and Dhib developed a nonlinear model predictive control scheme of a high‐pressure autoclave reactor.…”

Section: Introductionmentioning

confidence: 99%

Modeling of ethylene copolymerization in nonisothermal high‐pressure reactors using bifunctional initiators

Khazraei

Dhib

2018

Polymer Engineering & Sci

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Enhancing the performance of high-pressure LDPE process is valuable for polymer industry. However, the severe thermodynamics requirement of high pressure and temperature hinders the reaction process from getting simultaneously high monomer conversion and polymer molecular weights. Bifunctional peroxides used as initiators can boost the polymerization rate and alter rheological polymer properties. This article proposes a new kinetics model of ethylene/butyl acrylate copolymerization with bifunctional initiators in a high-pressure nonisothermal tubular reactor. Model predictions are compared with available data. A SQP optimization scheme is employed to determine a suitable wall temperature for each zone along the nonisothermal tubular reactor. In comparison with the monofunctional TBPPI peroxide, a lower amount of the bifunctional DHBPPI peroxide is needed to get a higher conversion in shorter residence time, but at the expense of higher thermal energy. The results also showed that polymers produced with bifunctional peroxides are significantly more branched. POLYM. ENG. SCI., 00:000-000, 2018.

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Unscented Kalman filter based nonlinear model predictive control of a LDPE autoclave reactor

Cited by 35 publications

References 34 publications

Nonlinear MPC of a multi-zone multi-feed LDPE autoclave reactor

Nonlinear MPC of a multi-zone multi-feed LDPE autoclave reactor

Projection based constrained nonlinear state estimation using Gaussian sum filters

Modeling of ethylene copolymerization in nonisothermal high‐pressure reactors using bifunctional initiators

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