Approximate robust optimization of nonlinear systems under parametric uncertainty and process noise

Andersson, 2012, CasADi – a symbolic package for automatic differentiation and optimal control Asprey, 2002, Designing robust optimal dynamic experiments, J. Process Control, 12, 545, 10.1016/S0959-1524(01)00020-8 Balsa-Canto, 2008, Computational procedures for optimal experimental design in biological systems, IET Syst. Biol., 2, 163, 10.1049/iet-syb:20070069 Biegler, 2007, An overview of simultaneous strategies for dynamic optimization, Chem. Eng. Process. Process Intensif., 46, 1043, 10.1016/j.cep.2006.06.021 Chachuat, 2004, A new approach in deterministic global optimisation of problems with ordinary differential equations., 83 Datskov, 2006, An approach to multicriteria optimization under uncertainty, Chem. Eng. Sci., 61, 2379, 10.1016/j.ces.2005.11.005 Diehl, 2008, Numerical solution approaches for robust nonlinear optimal control problems, Comput. Chem. Eng., 32, 1287, 10.1016/j.compchemeng.2007.06.002 Diwekar, 1997, Efficient sampling technique for optimization under uncertainty, Chem. Eng. Process., 43, 440 Ferreau, 2014, qpOASES: a parametric active-set algorithm for quadratic programming, Math. Program. Comput., 10.1007/s12532-014-0071-1 Galvanin, 2010, A backoff strategy for model-based experiment design under parametric uncertainty, AIChE J., 56, 2088 Gillis, 2013, A positive definiteness preserving discretization method for Lyapunov differential equations. Hannemann, 2010, Continuous and discrete adjoints for the Hessian of the Lagrangian in shooting algorithms for dynamic optimization, SIAM J. Sci. Comput., 31, 4675, 10.1137/080714518 Houska, 2009, Robust nonlinear optimal control of dynamic systems with affine uncertainties, 2274 Houska, 2011, ACADO Toolkit – an open-source framework for automatic control and dynamic optimization, Optim. Control Appl. Methods, 32, 298, 10.1002/oca.939 Houska, 2012, Robust optimization of nonlinear dynamic systems with application to a jacketed tubular reactor, J. Process Control, 22, 1152, 10.1016/j.jprocont.2012.03.008 Julier, 2002, The scaled unscented transformation, 4555 Julier, 1996 Kadam, 2007, Dynamic optimization in the presence of uncertainty: from off-line nominal solution to measurement-based implementation, J. Process Control, 17, 389, 10.1016/j.jprocont.2006.06.006 Kadam, 2007, Dynamic optimization in the presence of uncertainty: from off-line nominal solution to measurement-based implementation, J. Process Control, 17, 389, 10.1016/j.jprocont.2006.06.006 Kalman, 1961, New results in linear filtering and prediction theory, J. Basic Eng., 83, 95, 10.1115/1.3658902 Kawohl, 2007, A new approach for robust model predictive control of biological production processes, Chem. Eng. Sci., 62, 5212, 10.1016/j.ces.2007.01.003 Kim, 2013, Distributional uncertainty analysis using power series and polynomial chaos expansions, IEEE Control Syst. Mag., 58, 10.1109/MCS.2013.2270410 Li, 2008, Chance constrained programming approach to process optimization under uncertainty, Comput. Chem. Eng., 32, 25, 10.1016/j.compchemeng.2007.05.009 Logist, 2011, Robust multi-objective optimal control of uncertain (bio)chemical processes, Chem. Eng. Sci., 66, 4670, 10.1016/j.ces.2011.06.018 Logist, 2010, Efficient multiple objective optimal control of dynamic systems with integer controls, J. Process Control, 20, 810, 10.1016/j.jprocont.2010.04.009 Logist, 2008, Derivation of generic optimal reference temperature profiles for steady-state exothermic jacketed tubular reactors, J. Process Control, 18, 92, 10.1016/j.jprocont.2007.05.001 Logist, 2012, Multi-objective optimal control of chemical processes using ACADO toolkit, Comput. Chem. Eng., 37, 191, 10.1016/j.compchemeng.2011.11.002 Ma, 2003, Robust identification and control of batch processes, Comput. Chem. Eng., 1175, 10.1016/S0098-1354(03)00045-0 Maria, 2011, Derivation of optimal operating policies under safety and technological constraints for the acetoacetylation of pyrrole in a semi-batch catalytic reactor, Comput. Chem. Eng., 35, 177, 10.1016/j.compchemeng.2010.05.003 Mesbah, 2014, Stochastic nonlinear model predictive control with probabilistic constraints., 2413 Mitra, 2009, Multiobjective optimization of an industrial grinding operation under uncertainty, Chem. Eng. Sci., 64, 5043, 10.1016/j.ces.2009.08.012 Nagy, 2004, Open-loop and closed-loop robust optimal control of batch processes using distributional and worst-case analysis, J. Process Control, 14, 411, 10.1016/j.jprocont.2003.07.004 Nagy, 2006, Distributional uncertainty analysis using power series and polynomial chaos expansions, J. Process Control, 229 Papoulis, 1984 Pistikopoulos, 1995, Novel approach for optimal process design under uncertainty, Comput. Chem. Eng., 19, 1089, 10.1016/0098-1354(94)00093-4 Podmajersky, 2013, Measurement-based optimization of batch and repetitive processes using an integrated two-layer architecture, J. Process Control, 23, 943, 10.1016/j.jprocont.2013.05.003 Pontryagin, 1962 Recker, 2012, Sigmapoint approach for robust optimization of nonlinear dynamic systems., 199 Sahinidis, 2004, Optimization under uncertainty: state-of-the-art and opportunities, Comput. Chem. Eng., 28, 971, 10.1016/j.compchemeng.2003.09.017 Sargent, 2000, Optimal control, J. Comput. Appl. Math., 124, 361, 10.1016/S0377-0427(00)00418-0 Särkkä, 2007, On unscented Kalman filtering for state estimation of continuous-time nonlinear systems, IEEE Trans. Autom. Control, 52, 1631, 10.1109/TAC.2007.904453 Schenkendorf, 2009, Optimal experimental design with the sigma point method, IET Syst. Biol., 3, 10, 10.1049/iet-syb:20080094 Srinivasan, 2007, Real-time optimization of batch processes by tracking the necessary conditions of optimality, Ind. Eng. Chem. Res., 46, 492, 10.1021/ie0600487 Srinivasan, 2003, Dynamic optimization of batch processes II. Role of measurements in handling uncertainty, Comput. Chem. Eng., 27, 27, 10.1016/S0098-1354(02)00117-5 Stengel, 1986 Telen, 2013, Optimal experiment design under process noise using Riccati differential equations, J. Process Control, 23, 613, 10.1016/j.jprocont.2012.11.005 Telen, 2012, Optimal experiment design for dynamic bioprocesses: a multi-objective approach, Chem. Eng. Sci., 78, 82, 10.1016/j.ces.2012.05.002 Valappil, 2003, Accounting for batch reactor uncertainty in the nonlinear MPC of end-use properties, AIChE J., 49, 1178, 10.1002/aic.690490511 Van Der Merwe, 2004, Sigma-point kalman filters for nonlinear estimation and sensor-fusion: applications to integrated navigation. Wächter, 2006, On the implementation of a primal-dual interior point filter line search algorithm for large-scale nonlinear programming, Math. Progr., 106, 25, 10.1007/s10107-004-0559-y Wendt, 2002, Nonlinear chance-constrained process optimization under uncertainty, Ind. Eng. Chem. Res., 41, 3621, 10.1021/ie010649s