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Advanced Control Techniques
Last Updated: 2026-06-03 00:07:32
Abstract
Real-world control problems are complex and safety‑critical, so PID control often needs more advanced methods. This module covers modern techniques, starting with optimal control, which uses optimization to boost performance and reduce costs. We introduce MPC for fast, constrained control, and explore multiagent systems to manage large‑scale interactions efficiently.
Content
Real world control problems are often complex, saftety-critical, and performance oriented. That's why PID control alone might not be enough to guarantee performance and satisfy requirementes, and needs to be complemented by more sophisticated algorithms. In this module we explore modern control techniques that are the industry gold standard in several domains. We first introduce the general framework of optimal control, where optimization tools are used to maximize performance and minimizing costs. Model Predictive Control (MPC) is a powerful formulation to design fast on-line controllers which can handle constraint satisfaction for safetey guarantees. Finally, to break down the complex interactions and reduce the computatonal power needed to tackle large-scale problems, we discuss multiagent control systems.
General Information
- Language
- English
- Levels
- WBZ , NDS
- Frequency
- Yearly recurring
Examination
- Type
- ungraded semester performance
Registration & Places
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| lecture with exercise | Advanced Control Techniques | No time listed | 6 h semesterly |