http://etiennechassaing.com/tags/control/optimization/Control/OptimizationHugo Blox Builder (https://hugoblox.com)en-usFri, 01 Sep 2023 00:00:00 +0000http://etiennechassaing.com/media/icon_hub84619f942fe7a5590e3fd5bc84e624a_336037_512x512_fill_lanczos_center_3.pnghttp://etiennechassaing.com/tags/control/optimization/http://etiennechassaing.com/teaching/mpc/Fri, 01 Sep 2023 00:00:00 +0000http://etiennechassaing.com/teaching/mpc/<p><img src="featured.png" alt="Image alt"> <em>MPC principle</em></p> <h2 id="summary">Summary</h2> <p>This course provides the students with 1) a set of theoretical concepts to understand the machine learning approach; and 2) a subset of the tools to use this approach for problems arising in mechanical engineering applications.</p> <p>Provide an introduction to the theory and practice of Model Predictive Control (MPC). Main benefits of MPC: flexible specification of time-domain objectives, performance optimization of highly complex multivariable systems and ability to explicitly enforce constraints on system behavior.</p> <h2 id="content">Content</h2> <p>-Review of convex optimization and required optimal control theory.</p> <p>-Receding-horizon control for constrained linear systems.</p> <p>-Practical issues: Tracking and offset-free control of constrained systems.</p> <p>-Theoretical properties of constrained control: Constraint satisfaction and invariant set theory, Stability of MPC.</p> <p>-Introduction to advanced topics in predictive control.</p> <p>-Simulation-based project providing practical experience with MPC.</p> <p>Source : <a href="https://edu.epfl.ch/coursebook/en/model-predictive-control-ME-425">EPFL</a> <a href="https://fr.mathworks.com/help/mpc/gs/what-is-mpc.html">MathWorks</a></p>