The explicit linear quadratic regulator for constrained systems

http://cepac.cheme.cmu.edu/pasilectures/sahinidis/NVSpaperthree.pdf

Optimization under uncertainty: state-of-the-art and opportunities

Model Predictive Control (MPC), the dominant advanced control approach in industry over the past twenty-five years, is presented comprehensively in this unique book. With a simple, unified approach, and with attention to real-time implementation, it covers predictive control theory including the stability, feasibility, and robustness of MPC controllers. The theory of explicit MPC, where the nonlinear optimal feedback controller can be calculated efficiently, is presented in the context of linear systems with linear constraints, switched linear systems, and, more generally, linear hybrid systems. Drawing upon years of practical experience and using numerous examples and illustrative applications, the authors discuss the techniques required to design predictive control laws, including algorithms for polyhedral manipulations, mathematical and multiparametric programming and how to validate the theoretical properties and to implement predictive control policies. The most important algorithms feature in an accompanying free online MATLAB toolbox, which allows easy access to sample solutions. Predictive Control for Linear and Hybrid Systems is an ideal reference for graduate, postgraduate and advanced control practitioners interested in theory and/or implementation aspects of predictive control.

Predictive Control for Linear and Hybrid Systems

http://maranas.che.psu.edu/pub/2003/Gupta_and_Maranas,_Computers_and_Chemical_Engineering,_2003.pdf

Managing demand uncertainty in supply chain planning

Multiparametric Programming- Multiparametric Programming: a Geometric Approach- Optimal Control of Linear Systems- Constrained Finite Time Optimal Control- Constrained Infinite Time Optimal Control- Receding Horizon Control- Constrained Robust Optimal Control- Reducing On-line Complexity- Optimal Control of Hybrid Systems- Hybrid Systems- Constrained Optimal Control for Hybrid Systems- Applications- Ball and Plate- Traction Control

Constrained Optimal Control of Linear and Hybrid Systems

In this paper, a parametric programming approach is proposed for the analysis of linear process engineering problems under uncertainty. A novel branch and bound algorithm is presented for the solut...

Joaquín Acevedo

Papers

A multiparametric programming approach for linear process engineering problems under uncertainty

Stochastic optimization based algorithms for process synthesis under uncertainty

An optimization approach for process engineering problems under uncertainty

An algorithm for multiparametric mixed-integer linear programming problems

Computational studies of stochastic optimization algorithms for process synthesis under uncertainty