Syllabus

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

  1. 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.

  2. Lecture 2
     (i) Introduction to estimation problem and solution (Kalman filtering)
     (ii) Distributed optimization

  3. Lecture 3 - Introduction to distributed Kalman filter for linear stochastic state space model

  4. Lecture 4 - Cyber security in CPs in centralized and decentralized-framework

  5. Theme 1 presentations - Distributed Kalman Filtering for time-varying graphs

  6. Theme 2 presentations - Distributed optimization in power systems: Economic Dispatch Problem

  7. Theme 3 presentations - Cyber security in distributed framework etc.

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:

  Substitutes for Courses

Prerequisites

• valid for whole curriculum period:

  Prerequisites

FURTHER INFORMATION

Further Information

• valid for whole curriculum period:

  Teaching Language: English

Description