Robustly stable economic NMPC for non-dissipative stage costs

Abstract We analyze the inherent robustness properties of an economic NMPC formulation in which the controller trades off rate of convergence and economic performance. We show that this controller is input-to-state practically stable under reasonable assumptions. Our formulation does not require dissipativity with respect to the stage costs being optimized, as is required by existing economic MPC formulations. Instead, our formulation enforces dissipation in the form of a Lyapunov inequality that is constructed by using traditional tracking cost terms. Consequently, the proposed approach can be applied to a wider range of systems. We also demonstrate that the controller provides high flexibility to optimize economic performance and remains robust in the face of disturbances.

[1]  Lorenz T. Biegler,et al.  Control and optimization strategies for thermo-mechanical pulping processes: Nonlinear model predictive control , 2011 .

[2]  Victor M. Zavala,et al.  Optimization-based strategies for the operation of low-density polyethylene tubular reactors: nonlinear model predictive control , 2009, Comput. Chem. Eng..

[3]  Zhong-Ping Jiang,et al.  Input-to-state stability for discrete-time nonlinear systems , 1999 .

[4]  L. Biegler,et al.  Robust stability of economically oriented infinite horizon NMPC that include cyclic processes , 2012 .

[5]  Christos T. Maravelias,et al.  Economic model predictive control for inventory management in supply chains , 2014, Comput. Chem. Eng..

[6]  Dominique Bonvin,et al.  On turnpike and dissipativity properties of continuous-time optimal control problems , 2015, Autom..

[7]  Xuejin Yang,et al.  Advances in sensitivity-based nonlinear model predictive control and dynamic real-time optimization , 2015 .

[8]  Lorenz T. Biegler,et al.  Trajectory Bounds of Input-to-State Stability for Nonlinear Model Predictive Control∗ , 2015 .

[9]  David Angeli,et al.  On Necessity and Robustness of Dissipativity in Economic Model Predictive Control , 2015, IEEE Transactions on Automatic Control.

[10]  S. Skogestad DYNAMICS AND CONTROL OF DISTILLATION COLUMNS A tutorial introduction , 1997 .

[11]  Victor M. Zavala,et al.  Advanced step nonlinear model predictive control for air separation units , 2009 .

[12]  Stephen J. Wright,et al.  Numerical Optimization , 2018, Fundamental Statistical Inference.

[13]  Victor M. Zavala,et al.  Real-Time Nonlinear Optimization as a Generalized Equation , 2010, SIAM J. Control. Optim..

[14]  D. Limón,et al.  Input-to-State Stability: A Unifying Framework for Robust Model Predictive Control , 2009 .

[15]  Lars Grüne,et al.  On the relation between strict dissipativity and turnpike properties , 2016, Syst. Control. Lett..

[16]  S. Joe Qin,et al.  A survey of industrial model predictive control technology , 2003 .

[17]  Lorenz T. Biegler,et al.  Advanced-Multi-Step Nonlinear Model Predictive Control , 2013 .

[18]  Zhong-Ping Jiang,et al.  A converse Lyapunov theorem for discrete-time systems with disturbances , 2002, Syst. Control. Lett..

[19]  Victor M. Zavala,et al.  Economic nonlinear model predictive control for mechanical pulping processes , 2016, 2016 American Control Conference (ACC).

[20]  Stephen J. Wright,et al.  Conditions under which suboptimal nonlinear MPC is inherently robust , 2011, Syst. Control. Lett..

[21]  Lars Grüne,et al.  A Lyapunov function for economic MPC without terminal conditions , 2014, 53rd IEEE Conference on Decision and Control.

[22]  Lars Imsland,et al.  Combined economic and regulatory predictive control , 2016, Autom..

[23]  Dominique Bonvin,et al.  On the design of economic NMPC based on approximate turnpike properties , 2015, 2015 54th IEEE Conference on Decision and Control (CDC).

[24]  Victor M. Zavala,et al.  The advanced-step NMPC controller: Optimality, stability and robustness , 2009, Autom..

[25]  Brian W. Kernighan,et al.  AMPL: A Modeling Language for Mathematical Programming , 1993 .

[26]  Eduardo Sontag Smooth stabilization implies coprime factorization , 1989, IEEE Transactions on Automatic Control.

[27]  Jay H. Lee,et al.  Constrained linear state estimation - a moving horizon approach , 2001, Autom..

[28]  L. Biegler,et al.  Nonlinear Programming Properties for Stable and Robust NMPC , 2015 .

[29]  Roald Bræck Leer Self-Optimizing Control Structures for Active Constraint Regions of a Sequence of Distillation Columns , 2012 .

[30]  Lorenz T. Biegler,et al.  On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programming , 2006, Math. Program..

[31]  Lars Grne,et al.  Nonlinear Model Predictive Control: Theory and Algorithms , 2011 .

[32]  Panagiotis D. Christofides,et al.  Economic model predictive control of nonlinear process systems using Lyapunov techniques , 2012 .

[33]  V. Zavala A Multiobjective Optimization Perspective on the Stability of Economic MPC , 2015 .

[34]  L. Biegler,et al.  Fast economic model predictive control based on NLP-sensitivities , 2014 .

[35]  Victor M. Zavala,et al.  Stability of multiobjective predictive control: A utopia-tracking approach , 2012, Autom..

[36]  David Angeli,et al.  Fundamentals of economic model predictive control , 2012, 2012 IEEE 51st IEEE Conference on Decision and Control (CDC).

[37]  T. Badgwell A Robust Model Predictive Control Algorithm for Stable Nonlinear Plants , 1997 .

[38]  Moritz Diehl,et al.  A Lyapunov Function for Economic Optimizing Model Predictive Control , 2011, IEEE Transactions on Automatic Control.

[39]  Lars Grüne,et al.  Economic receding horizon control without terminal constraints , 2013, Autom..

[40]  Jacques Gauvin,et al.  A necessary and sufficient regularity condition to have bounded multipliers in nonconvex programming , 1977, Math. Program..

[41]  Xue Yang,et al.  Advanced-Multi-Step and Economically Oriented Nonlinear Model Predictive Control , 2015 .

[42]  A. Shapiro Sensitivity analysis of nonlinear programs and differentiability properties of metric projections , 1988 .