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You searched for +publisher:"Penn State University" +contributor:("Antonios Armaou, Dissertation Advisor"). One record found.

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Penn State University

1. Hashemian, Seyedeh Negar. ESTIMATION AND CONTROL OF TWO-COMPONENT GRANULATION PROCESSES.

Degree: 2017, Penn State University

There are many systems in different fields which consist of particle populations such as crystallization, polymerization, granulations and viral infections. The particles in these systems are characterized by their properties e.g. type, size and/or composition. Mostly, the governing equation for these dispersed systems includes a population balance resulting in an equation that involves both integrals and derivatives of an unknown function called integro-differential equation. In general, there is no analytical solution for these types of dynamic systems. This paper studies one of this particulate processes has been enhanced for application in the pharmaceutical industry; two-component high shear granulation. In this process, the granules are stuck together and form bigger particles through use of inactive binder droplets called excipient. In an ideal granulation process the composition and size of produced granules is the same, however, in reality the particle size and composition are distributed over a range.We address the issue of state estimation and control of a stochastic particulate process through (i) using model reduction to obtain a tractable approximation of the governing dynamics, (ii) designing a fast moving-horizon estimator for the reduced-order model and (iii) developing a Stochastic Model Predictive Control (SMPC) for the system. We first use the method of moments to reduce the governing integro-differential equation down to a nonlinear ordinary differential equation (ODE). In order to simplify the results of the method of moments, we exploit Taylor expansion and derive a closed finite-dimensional ordinary differential equation set. However, this approach cannot be used for composition-dependent models. To address this issue, this dissertation proposes a new model reduction approach using the method of moments in conjunction with Laguerre polynomials. In this way, we expand the distribution function over the set of orthogonal Laguerre polynomials which are function of moments. Also, we evaluate our new reduced models with the results obtained from a Monte Carlo simulation as a bench mark. These models will be the foundation for efficient observer and controller design for such bi-component agglomeration processes. Next, the states of the reduced order model are estimated in a Moving Horizon Estimation (MHE) approach. MHE is an optimization-based technique to estimate the unmeasurable state variables of a nonlinear dynamic system with noise in transition and measurement. One of the advantages of MHE over Extended Kalman Filter, the alternative approach in this area, is that it considers the physical constraints in its formulation. However, to offer this feature, MHE needs to solve a constrained nonlinear dynamic optimization problem which slows down the estimation process. In this work, we introduce and employ the Carleman approximation method in MHE design to accelerate the solution of the optimization problem. The Carleman method approximates the nonlinear system with a polynomial system at a… Advisors/Committee Members: Antonios Armaou, Dissertation Advisor.

Subjects/Keywords: Moving Horizon Estimation; Two Component Granulation; Monte Carlo Simulation; Carleman Approximation; Laguerre polynomials; Stochastic Model Predictive Control; Polynomial Chaos; Method of Moments; Soft Sensor; Fluid Bed Dryer; Pharmaceutical Processes; Model Order Reduction

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APA (6th Edition):

Hashemian, S. N. (2017). ESTIMATION AND CONTROL OF TWO-COMPONENT GRANULATION PROCESSES. (Thesis). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/13993suh245

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Hashemian, Seyedeh Negar. “ESTIMATION AND CONTROL OF TWO-COMPONENT GRANULATION PROCESSES.” 2017. Thesis, Penn State University. Accessed February 18, 2019. https://etda.libraries.psu.edu/catalog/13993suh245.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Hashemian, Seyedeh Negar. “ESTIMATION AND CONTROL OF TWO-COMPONENT GRANULATION PROCESSES.” 2017. Web. 18 Feb 2019.

Vancouver:

Hashemian SN. ESTIMATION AND CONTROL OF TWO-COMPONENT GRANULATION PROCESSES. [Internet] [Thesis]. Penn State University; 2017. [cited 2019 Feb 18]. Available from: https://etda.libraries.psu.edu/catalog/13993suh245.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Hashemian SN. ESTIMATION AND CONTROL OF TWO-COMPONENT GRANULATION PROCESSES. [Thesis]. Penn State University; 2017. Available from: https://etda.libraries.psu.edu/catalog/13993suh245

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

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