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Predictive Control With Constraints
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TLDR
A standard formulation of Predictive Control is presented, with examples of step response and transfer function formulations, and a case study of robust predictive control in the context of MATLAB.Abstract:
1. Introduction to Predictive Control. 2. A Standard Formulation of Predictive Control. 3. Solving Predictive Control Problems. 4. Step Response and Transfer Function Formulations. 5. Tuning. 6. Stability. 7. Robust Predictive Control. 8. Perspectives. 9. Case Studies. 10. The Model Predictive Control Toolbox. References Appendices A. Some Commercial MPC Products B. MATLAB Program basicmpc C. The MPC Toolbox D. Solutions to Problemsread more
Citations
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Proceedings ArticleDOI
YALMIP : a toolbox for modeling and optimization in MATLAB
TL;DR: Free MATLAB toolbox YALMIP is introduced, developed initially to model SDPs and solve these by interfacing eternal solvers by making development of optimization problems in general, and control oriented SDP problems in particular, extremely simple.
Journal ArticleDOI
A survey of industrial model predictive control technology
S. Joe Qin,Thomas A. Badgwell +1 more
TL;DR: An overview of commercially available model predictive control (MPC) technology, both linear and nonlinear, based primarily on data provided by MPC vendors, is provided in this article, where a brief history of industrial MPC technology is presented first, followed by results of our vendor survey of MPC control and identification technology.
Book
Model Predictive Control
TL;DR: This paper recalls a few past achievements in Model Predictive Control, gives an overview of some current developments and suggests a few avenues for future research.
Journal ArticleDOI
Predictive Control in Power Electronics and Drives
TL;DR: A simple classification of the most important types of predictive control is introduced, and each one of them is explained including some application examples.
Journal ArticleDOI
Fast Model Predictive Control Using Online Optimization
Yang Wang,Stephen Boyd +1 more
TL;DR: A collection of methods for improving the speed of MPC, using online optimization, which can compute the control action on the order of 100 times faster than a method that uses a generic optimizer.