A novel analytical second‐order sensitivity calculation approach using the finite element method for chemical engineering problems

[1]  Z. Qi,et al.  Multi-objective optimization method for enhancing chemical reaction process , 2019, Chemical Engineering Science.

[2]  Shurong Li,et al.  An iterative dynamic programming optimization based on biorthogonal spatial-temporal Hammerstein modeling for the enhanced oil recovery of ASP flooding , 2019, Journal of Process Control.

[3]  Jorge Nocedal,et al.  An Interior Point Algorithm for Large-Scale Nonlinear Programming , 1999, SIAM J. Optim..

[4]  Eva Balsa-Canto,et al.  Dynamic optimization of chemical and biochemical processes using restricted second order information , 2001 .

[5]  D. J. Gunn,et al.  Mass transport and chemical reaction in multifunctional catalyst systems , 1965 .

[6]  Michael Mahon,et al.  Application and optimisation studies of a zinc electrowinning process simulation , 2014 .

[7]  Xin Wang,et al.  Integral fractional pseudospectral methods for solving fractional optimal control problems , 2015, Autom..

[8]  Anil V. Rao,et al.  Direct Trajectory Optimization Using a Variable Low-Order Adaptive Pseudospectral Method , 2011 .

[9]  V. Vassiliadis,et al.  Second-order sensitivities of general dynamic systems with application to optimal control problems , 1999 .

[10]  Rui Su,et al.  Real-Time Trajectory and Attitude Coordination Control for Reusable Launch Vehicle in Reentry Phase , 2015, IEEE Transactions on Industrial Electronics.

[11]  Weihua Gui,et al.  Sensitivity-based adaptive mesh refinement collocation method for dynamic optimization of chemical and biochemical processes , 2017, Bioprocess and Biosystems Engineering.

[12]  Ping Liu,et al.  Novel non-uniform adaptive grid refinement control parameterization approach for biochemical processes optimization , 2016 .

[13]  Kapil Gupta,et al.  Dynamic Optimization of Chemical Processes using Ant Colony Framework , 2001, Comput. Chem..

[14]  Guodong Li,et al.  Comments on “Optimal Use of Mixed Catalysts for Two Successive Chemical Reactions” , 2015, J. Optim. Theory Appl..

[15]  Rein Luus,et al.  On solving optimal control problems with free initial condition using iterative dynamic programming , 2001 .

[16]  Qi Gong,et al.  A pseudospectral method for the optimal control of constrained feedback linearizable systems , 2006, IEEE Transactions on Automatic Control.

[17]  Jorge Nocedal,et al.  An interior algorithm for nonlinear optimization that combines line search and trust region steps , 2006, Math. Program..

[18]  William W. Hager,et al.  Pseudospectral methods for solving infinite-horizon optimal control problems , 2011, Autom..

[19]  K. Saberyan,et al.  Analytical and semi-analytical kinetics models for design and optimization of double-resistance resin in pulp and carbon in pulp processes with both reversible and irreversible nature , 2018 .

[20]  Xinggao Liu,et al.  An efficient interior-point algorithm with new non-monotone line search filter method for nonlinear constrained programming , 2017 .

[21]  Günter Wozny,et al.  An efficient sparse approach to sensitivity generation for large-scale dynamic optimization , 2011, Comput. Chem. Eng..

[22]  Liang Ma,et al.  An effective pseudospectral method for constraint dynamic optimisation problems with characteristic times , 2018, Int. J. Control.

[23]  Jorge Nocedal,et al.  Interior Methods for Mathematical Programs with Complementarity Constraints , 2006, SIAM J. Optim..

[24]  James E. Bobrow,et al.  An efficient sequential linear quadratic algorithm for solving nonlinear optimal control problems , 2005, Proceedings of the 2005, American Control Conference, 2005..

[25]  R. Irizarry.  A generalized framework for solving dynamic optimization problems using the artificial chemical process paradigm: Applications to particulate processes and discrete dynamic systems , 2005 .

[26]  Bangjun Lei,et al.  Hybrid stochastic optimization method for optimal control problems of chemical processes , 2017 .

[27]  Michael A. Saunders,et al.  SNOPT: An SQP Algorithm for Large-Scale Constrained Optimization , 2002, SIAM J. Optim..

[28]  Shiming He,et al.  An adaptive pseudospectral method for constrained dynamic optimization problems in chemical engineering , 2016 .

[29]  Y. A. Liu,et al.  An effective computational algorithm for suboptimal singular and/or bang-bang control I. Theoretical developments and applications to linear lumped systems , 1976 .

[30]  D. Ruthven,et al.  Numerical simulation of a pressure swing air separation systemndasha comparative study of finite difference and collocation methods , 1987 .

[31]  Ping Liu,et al.  A novel fast dynamic optimization approach for complex multivariable chemical process systems , 2016 .

[32]  Di Wu,et al.  A new computational approach for optimal control problems with multiple time-delay , 2019, Autom..

[33]  S. A. Dadebo,et al.  Dynamic optimization of constrained chemical engineering problems using dynamic programming , 1995 .

[34]  Paul I. Barton,et al.  Large-Scale Dynamic Optimization Using the Directional Second-Order Adjoint Method , 2005 .

[35]  R. Luus.  Optimal control by dynamic programming using systematic reduction in grid size , 1990 .

[36]  Lorenz T. Biegler,et al.  Convergence rates for direct transcription of optimal control problems using collocation at Radau points , 2008, Comput. Optim. Appl..

[37]  Pu Li,et al.  An Analytical Hessian and Parallel-Computing Approach for Efficient Dynamic Optimization Based on Control-Variable Correlation Analysis , 2015 .

[38]  Jinxing Lin,et al.  A switched dynamical system approach towards the optimal control of chemical processes based on a gradient-based parallel optimization algorithm , 2018, Comput. Chem. Eng..

[39]  M. Rahimpour,et al.  Modeling and optimal control of conversion section of styrene plant to overcome effect of catalyst deactivation on production capacity , 2018, Chemical Engineering Research and Design.

[40]  Stephen L. Campbell,et al.  Solving optimal control problems with control delays using direct transcription , 2016 .

[41]  Xinggao Liu,et al.  An effective pseudospectral optimization approach with sparse variable time nodes for maximum production of chemical engineering problems , 2017 .