LEARNING OUTCOMES
Credits: 3
Schedule: 21.10.2024 - 25.11.2024
Teacher in charge (valid for whole curriculum period):
Teacher in charge (applies in this implementation): Simo Särkkä, Muhammad Iqbal, Kundan Kumar
Contact information for the course (applies in this implementation):
Instructors can be contacted via email.- Muhammad Iqbal - muhammad.iqbal@aalto.fi
- Kundan Kumar - kundan.kumar@aalto.fi
CEFR level (valid for whole curriculum period):
Language of instruction and studies (applies in this implementation):
Teaching language: English. Languages of study attainment: English
CONTENT, ASSESSMENT AND WORKLOAD
Content
valid for whole curriculum period:
This seminar course introduces distributed estimation and control in cyber-physical systems (CPS), focusing on key applications such as power systems, critical infrastructure, and intelligent transportation. It begins with foundational concepts in graph theory, consensus control, and estimation techniques like Kalman filtering, before progressing into distributed optimization methods. The course places particular emphasis on distributed Kalman filtering for linear stochastic state-space models and addresses the unique challenges of cyber security in both centralized and decentralized frameworks. Students will prepare presentations on topics including, but not limited to, distributed Kalman filtering on time-varying graphs, optimization in power systems through the economic dispatch problem, and cyber security in distributed environments.
applies in this implementation
- Lecture 1
(i) Motivation (Distributed estimation and control of cyber-physical systems (CPs))a) Examples include power systems, critical infrastructure, intelligent transportation etc.
b) Goals
(ii) Introduction to graph theory, consensus control etc. Lecture 2
(i) Introduction to estimation problem and solution (Kalman filtering)
(ii) Distributed optimizationLecture 3 - Introduction to distributed Kalman filter for linear stochastic state space model
Lecture 4 - Cyber security in CPs in centralized and decentralized-framework
Theme 1 presentations - Distributed Kalman Filtering for time-varying graphs
Theme 2 presentations - Distributed optimization in power systems: Economic Dispatch Problem
Theme 3 presentations - Cyber security in distributed framework etc.
- Lecture 1
Assessment Methods and Criteria
applies in this implementation
In this seminar course, the evaluation criteria will be based on the presentation of the above-mentioned themes. In the last three sessions, a team of students (not more than three) will give presentations on their selected topics.
DETAILS
Study Material
applies in this implementation
- Simo Särkkä and Lennart Svensson, Bayesian Filtering and Smoothing, 2nd ed. Cambridge University Press, 2023.
- Francesco Bullo, Jorge Cortés, Florian Dörfler, and Sonia Martínez, Lecture on Network System, vol. 1, 2018.
Substitutes for Courses
valid for whole curriculum period:
Prerequisites
valid for whole curriculum period:
FURTHER INFORMATION
Further Information
valid for whole curriculum period:
Teaching Language: English