Wahlpflichtfächer

Course content:
I. Introduction,
1.1 What is MPC?
1.2 Optimal Prediction
2. I/O approach
2.1 Minimum Variance Control
2.2 1-step ahead prediction
2.3 1-step ahead prediction with frequency weighting
3. Generalized predictive Control
3.1. Optimal prediction for control design purposes
3.2 Criteria and solution of the optimization problem
3.3 Linear Time Invariant Controller
3.4 Input/Output performances

Learning objectives:
Subject-specific competencies: Students
• can distinguish between I/O and state space approach
• can implement a j-step ahead predictor
• know the two degree of freedom control structure for MPC
• can implemented a generalized predictive controller

Methodological competencies: Students
• can select and apply suitable methods to solve discrete time control problems
• Gain a general understanding of MPC in the frequency domain
• obtain a portfolio of various design methods and tools

Interdisciplinary competencies: Students
• further develop their English language skills
• are used to be taught by an international instructor
• have gained intercultural experiences