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This is the MATLAB code for a brief tutorial for Model Predictive Control (MPC) for a linear discrete-time system with constrained states and inputs.

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MPC Tutorial

This tutorial (https://arxiv.org/abs/2109.11986) shows an overview of Model Predictive Control with a linear discrete-time system and constrained states and inputs. The focus is on the implementation of the method under consideration of stability and recursive feasibility.

  • Example1.m: Simple example of the regulation probelm with a discrete-time double-integrator system
  • Example2.m: This example demonstrate the loss of feasiblity.
  • Example3.m: In this example, the recursive feasiblity is guaranteed due to a terminal constraint. This terminal constraints is computed at the beginning.

In this Tutorial, the MPT3 Toolbox is used. (M. Herceg, M. Kvasnica, C.N. Jones, and M. Morari. Multi-Parametric Toolbox 3.0. In Proc. of the European Control Conference, pages 502–510, Zurich, Switzerland, July 17–19 2013. https://www.mpt3.org/ )

The plots are created with matlab2tikz (https://github.com/matlab2tikz/matlab2tikz).

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This is the MATLAB code for a brief tutorial for Model Predictive Control (MPC) for a linear discrete-time system with constrained states and inputs.

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