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Dynamic optimization of constrained semi-batch processes using Pontryagin's minimum principle—An effective quasi-Newton approach

Erdal Aydin, Dominique Bonvin, Kai Sundmacher
2017 Computers and Chemical Engineering  
This work considers the numerical optimization of constrained batch and semi-batch processes, for which direct as well as indirect methods exist.  ...  Indirect methods, such as Pontryagin's Minimum Principle (PMP), reformulate the optimization problem.  ...  CONCLUSIONS A PMP-based quasi-Newton algorithm has been proposed for solving constrained dynamic optimization of semi-batch chemical processes.  ... 
doi:10.1016/j.compchemeng.2017.01.019 fatcat:kwjalvwgsjg2da2wzoqqfjoqly

Dynamic optimization of batch processes

B. Srinivasan, S. Palanki, D. Bonvin
2003 Computers and Chemical Engineering  
The optimization of batch processes has attracted attention in recent years because, in the face of growing competition, it is a natural choice for reducing production costs, improving product quality,  ...  This characterization is key to the utilization of measurements in an optimization framework, which will be the subject of the companion paper. #  ...  Acknowledgements The authors would like to thank the anonymous reviewer, whose helpful comments have been used to improve this paper, and the Swiss National Science Foundation, grant number 21-46922.96  ... 
doi:10.1016/s0098-1354(02)00116-3 fatcat:eujctrfff5hnjfoewj47r2mcgu

Control and Optimization of Batch Chemical Processes [chapter]

Dominique Bonvin, Grégory François
2017 Coulson and Richardson's Chemical Engineering  
Several case studies are presented to illustrate the various approaches Keywords Batch control, predictive control, iterative learning control, run-to-run control, batch process optimization, dynamic optimization  ...  A batch process is characterized by the repetition of time-varying operations of finite duration.  ...  René Schneider who provided useful feedback on the manuscript.  ... 
doi:10.1016/b978-0-08-101095-2.00011-4 fatcat:tkhqz7kiw5cpnlllwcw6qoamzi

2020 Index IEEE Transactions on Automatic Control Vol. 65

2020 IEEE Transactions on Automatic Control  
., +, TAC Jan. 2020 130-142 Combining Pontryagin's Principle and Dynamic Programming for Linear and Nonlinear Systems.  ...  ., +, TAC Jan. 2020 115-129 Combining Pontryagin's Principle and Dynamic Programming for Linear and Nonlinear Systems.  ...  Linear programming A Decentralized Event-Based Approach for Robust Model Predictive Control.  ... 
doi:10.1109/tac.2020.3046985 fatcat:hfiqhyr7sffqtewdmcwzsrugva

Retrospective on optimization

Lorenz T. Biegler, Ignacio E. Grossmann
2004 Computers and Chemical Engineering  
We also review their extensions to dynamic optimization and optimization under uncertainty.  ...  process systems engineering.  ...  Dynamic optimization using collocation methods has been used for a number of process applications including batch process optimization (Bhatia & Biegler, 1996) , nonlinear model predictive control (Albuquerque  ... 
doi:10.1016/j.compchemeng.2003.11.003 fatcat:4y43k7pcufh47jzdkm32enkx3a

Thermal processing and quality: Principles and overview

G.B. Awuah, H.S. Ramaswamy, A. Economides
2007 Chemical Engineering and Processing  
New processing concepts such as the application of variable retort temperature have received attention from processing experts and promises to improve both the economy and quality of thermally processed  ...  The food processing industry has matured over the years with an impressive record on safety and a vibrant marketplace for new product development.  ...  Optimization methods that have been used for food-related research include (i) the Pontryagin's maximum principle theory [69] , (ii) optimization algorithm based on non-linear programming [58] , (iii  ... 
doi:10.1016/j.cep.2006.08.004 fatcat:k6qymoztbrf2bkkcapdy74wehy

Computational Air Traffic Management

Marc Anthony Azzopardi, James F. Whidborne
2011 2011 IEEE/AIAA 30th Digital Avionics Systems Conference  
transportation system based on optimisation principles.  ...  This work advances the field of ATM as well as the fields of Computational Intelligence and Dynamic Optimisation of High Dimensionality Non-Convex Search Spaces. iii DEDICATIONS To my brother Carl, my  ...  Subject to: -First order dynamic constraints: Pontryagin's minimum principle (PMP) provides the necessary (but insufficient) conditions to achieve optimality [4.2].  ... 
doi:10.1109/dasc.2011.6095967 fatcat:5kfu6ba5h5g7pdffh7z3ftdjai

Tailored indirect algorithms for efficient on-line optimization of batch and semi-batch processes [article]

Erdal Aydin, Universitäts- Und Landesbibliothek Sachsen-Anhalt, Martin-Luther Universität, Kai Sundmacher, Sebastian Sager
Alternatively, indirect methods based on Pontryagin's Minimum Principle (PMP) could efficiently deal with the optimization of batch and semi-batch processes.  ...  Dynamic optimization plays an important role toward improving the operation of batch and semi-batch processes.  ...  Summary A PMP-based quasi-Newton algorithm has been proposed for solving constrained dynamic optimization of batch and semi-batch chemical processes.  ... 
doi:10.25673/12290 fatcat:tqyiy6zx2nb43h6xrxoeuff6re

Certifying Unstability of Switched Systems Using Sum of Squares Programming

Benoît Legat, Pablo Parrilo, Raphaël Jungers
2020 SIAM Journal of Control and Optimization  
Signal Process., 10(4):757-769, 2016. [2] 4 Acknowledgements We can generalize these result when the allowed switching sequences of the system (1) are constrained by an automaton.  ...  Specifically, we focus on the interpretation of the timescales involved in such a process.  ...  Since the dynamics are linear and the objective function is convex, the problem can be solved using Pontryagin's Minimum Principle [2] , resulting in the optimal input u * as a function of the initial  ... 
doi:10.1137/18m1173460 fatcat:ytlzbwk7vbampbuyo6snenz33m

Geometric Optimal Control of the Contrast Imaging Problem in Nuclear Magnetic Resonance

B. Bonnard, O. Cots, S. J. Glaser, M. Lapert, D. Sugny, Yun Zhang
2012 IEEE Transactions on Automatic Control  
Optimal trajectories can be selected among extremal solutions of the Pontryagin Maximum Principle applied to this Mayer type optimal problem.  ...  Hence the optimal problem is reduced to the analysis of the Hamiltonian dynamics related to singular extremals and their optimality status.  ...  Table 3 .1 Fluid case: Batch optimizations (Direct method).  ... 
doi:10.1109/tac.2012.2195859 fatcat:jm6jt66pijbjxmxxbfgtxwieqy

Fast numerical methods for robust nonlinear optimal control under uncertainty

Lilli Bergner
For more information and for the numerical solution of semi-implicit index one DAE systems, we refer to [3, 4, 12, 118] Pontryagin's minimum principle Pontryagin's minimum principle of optimal control  ...  We assume that the optimal control function u is non-singular and can hence be determined using Pontryagin's minimum principle.  ...  B.2 Nonlinear programming problems Adaptive polynomial chaos for optimal control . .  ... 
doi:10.11588/heidok.00024212 fatcat:jxsp42wx2jg7leuzmqrutq37oe

Integration of Scheduling and Dynamic Optimization: Computational Strategies and Industrial Applications

Yisu Nie
This thesis study focuses on the development of model-based optimization strategies for the integration of process scheduling and dynamic optimization, and applications of the integrated approaches to  ...  We develop rigorous dynamic reactor models for both semi-batch homopolymerization and copolymerization operations.  ...  Solution Approaches for Dynamic Optimization Analytical solution of the dynamic optimization problem requires applying Pontryagin's maximum principle or solving Hamilton-Jacobi-Bellman equations, which  ... 
doi:10.1184/r1/6720260.v1 fatcat:t3hhirr4ajge7omh3ybxy54324

Self-Modeling Neural Systems

Gregory D. Wayne
an optimal feedback controller.  ...  In this dissertation, we use the framework of optimal control theory to model goal-directed behavior and repurpose it in new ways.  ...  Optimization of the network parameters was accomplished using batch training with the quasi-Newton optimization method L-BFGS in "minFunc" by Mark Schmidt.  ... 
doi:10.7916/d8fx7hvf fatcat:dqdkkzyzk5gwhhsvalhvbiwrwu

Framework for online modeling, optimization and monitoring of bioprocesses [article]

Ezequiel Franco Lara, Universitäts- Und Landesbibliothek Sachsen-Anhalt, Martin-Luther Universität
The optimization task is fulfilled using an evolutionary procedure: first actualization of a model based on available information and a priori knowledge; the actualized approach was used in a model-based  ...  The methodology is first exemplified with the off-line modeling and optimization of the production of the viral capsid complex VP1-DHFR using a strain of Escherichia coli BL21 under fed-batch conditions  ...  Moreover, the use of classical methods like dynamical programming or Pontryagin's maximum principle is commonly restricted to simple models (Pontryagin et al., 1962; Park and Ramirez, 1988) .  ... 
doi:10.25673/3145 fatcat:26zqqnt7onha7ntn4ydrrap6e4

A direct method for the numerical solution of optimization problems with time-periodic PDE constraints

Andreas Potschka
compared to the use of the exact Lagrangian Hessian.  ...  Moreover we extend the inexact Newton method to an inexact Sequential Quadratic Programming (SQP) method for inequality constrained problems and provide local convergence theory.  ...  Inequality constrained optimization problems We have developed an approach how inequality constrained optimization problems can be treated on the basis of an NMT LISA-Newton method (see Section 6).  ... 
doi:10.11588/heidok.00012993 fatcat:2jf7ufj3fbfadehdpjazvbzvby
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