Computational Sciences Center

etit-523: Optimization and Optimal Control


Many problems industry and economy rely on the determination of an optimal solution satisfying desired performance criteria and constraints. In mathematical terms this leads to the formulation of an optimization problem. Here it is in general distinguished between static and dynamic optimization with the latter involving a dynamical process. This lecture gives an introduction to the mathematical analysis and numerical solution of static and dynamic optimization problems with a particular focus on optimal control problems. The lecture addresses the following topics:

  • Fundamentals of static and dynamic optimization problems
  • Static optimization without and with constraints
  • Dynamic optimization without and with constraints
  • Model predictive control




[1] S. Boyd, L. Vandenberghe: Convex Optimization, Cambridge University Press. [2] A.E. Bryson: Dynamic Optimization, Addison-Wesley. [3] L. Grüne, J. Pannek: Nonlinear Model Predictive Control: Theory and Algorithms, Springer. [4] D.G. Luenberger, Y. Ye: Linear and Nonlinear Programming, Springer. [5] J. Nocedal, S.J. Wright: Numerical Optimization, Springer. [6] M. Papageorgiou: Optimierung, Oldenbourg Verlag.

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