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IfA Open House

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Abstract:
On Tuesday, December 2nd 2014, the Automatic Control Laboratory (IfA) would like to welcome all students interested in automatic control to the IfA Open House.
The event starts at 4.15pm in ETF E1 with an introduction to the different groups in our lab given by the four IfA professors: John Lygeros, Manfred Morari, Florian Dörfler, and Roy Smith. Following the introduction, there will be different stations where current research topics are presented. We would like to encourage you to take this opportunity to get in touch with members of IfA and find interesting semester and master projects. The event ends with a closing apero in ETL K25.

Time Schedule
4:15 - 5:00pm: presentations by professors (ETF E1)
5:00 - 6:15pm: various stations showcasing the current research topics (logistics to be explained on the day)

Research Station Descriptions
The following gives a short description of the stations that will be showcasing the current research topics from the lab.

Control of Electrical Drives and Compressors

The optimization of the operations of electrical drives is a topic of paramount importance when considering energy efficiency of industrial plants. We present recent work in advanced models for power losses in induction motors, based on magnetic modeling. Optimal control operation can further improve the efficiency of the energy transformation.
More information available here


Autonomous Sailing

The aim of the autonomous sailing project is to develop the IfA autonomous model sailboat to participate in the next robotic sailing world championship. Interdisciplinary semester and master projects are available in two main areas:
  1. sensor fusion and state estimation to design algorithms processing information from the onboard sensors
  2. optimal path planning and tracking to control the sail boat according to the given tasks, including the regatta race. The main challenges are the highly nonlinear system dynamics and the limited actuation capabilities
All the projects consist of hardware and software developments
More information available here


Population control of large-scale smart energy system

Macroscopic incentives can control large-size populations of energy-related dynamical systems, such as electric vehicles, flexible household appliances and renewable energy sources. The optimal responses of the individual systems to these incentives may result in an aggregate population behaviour which is beneficial for the overall power grid. Related student projects will cover both theoretical and computational aspects.
More information available here


RoboCup, the Z-Knipsers

RoboCup promotes research in the fields of robotics and artificial intelligence through the game of soccer. The ultimate goal is challenging the human World Cup champions with robots by 2050. Our team, the Z-Knipsers, successfully participated at their first international tournament the German Open this year. At a second tournament we came in second. However, a range of challenges emerged. This semester students are working on improved self-localization, passing, motor control and dynamic role assignment. These students will give a brief overview of their work and highlight future opportunities for projects.
More information available here


Control of Power Electronics Systems

Technological advancements in power electronics and control hardware enable new, exciting applications and performance improvements in existing applications. These advancements rely on effective control algorithms and good models. Therefore it is essential to properly characterize and identify the controlled systems, as well as to select an appropriate control scheme. Applications range from very low power (consumer electronics) to medium (drives, compressors) to very high power systems (trains, turbines, power lines).
More information available here


Airborne Wind Energy

The aim of the airborne wind energy project is to achieve fully-autonomous flight of kites for power generation. Such kite systems exhibit highly nonlinear dynamics and are limited to ground-based actuation and sensing. To tackle these challenges we offer Semester and Master project in:
  1. Conceptual design of a kite power generator for optimal power output;
  2. GUI for real-time simulation environment of kites;
  3. Design and development of a one-line kite power test platform.
Most projects provide a balance between hardware and theoretical development and consist of a strong experimental component during field tests at different locations in Switzerland (limited to Spring and Summer months).
For more information check out: http://control.ee.ethz.ch/~awe.


Thermoacoustic cooler as an example of a thermoacoustic machine

Thermoacoustic machines convert thermal energy into sound waves which in turn can drive thermoacoustic cooler or can be directly converted into electrical energy using an electrodynamic transduction mechanism. Such machines have a high potential for the development of clean, sustainable and alternative energy systems by utilizing low temperature waste heat recovery, biomass and gas combustion heat and solar energy, respectively.
More information available here


Model Predictive Building Climate Control

Approximately 40% of the global used energy is consumed in buildings, of which roughly half is used for Heating, Ventilation and Air Conditioning (HVAC). At the same time, most investments in building energy efficiency can be expected to pay back through reduced energy bills.
Model Predictive Control (MPC) is a promising alternative to standard strategies for building control. MPC uses a mathematical model of the building and predictions of disturbances (e.g., ambient temperature) over a given prediction horizon (e.g., two days) for defining an optimization problem that is solved such as to maintain thermal comfort for the occupants while minimizing some objective (e.g., energy use or monetary cost). This makes it possible to integrate all available actuators and their interactions as well as predictions of weather, internal gains and electricity prices into a coherent, mathematical control framework that can handle constraints on control inputs and room temperatures.
At IfA we focus on practical issues in the implementation of MPC on buildings, develop software for fast modelling of buildings, perform simulation studies and develop novel MPC formulations that enable an improved performance.
More information available here


Stochastic Control

Model Predictive Control (MPC) is a popular model-based methodology to synthesize optimal controllers for deterministic systems. In practice, however, plant models are rarely known precisely, and systems are influenced by disturbances. In this case, it is important to take these uncertainties into account when designing controllers, which can be accomplished using Stochastic MPC or Approximate Dynamic Programming.
At the station we will give a brief overview on this topic and present existing projects.
More information available here


Autonomous Helicopters

The RCopterX project aims at automatic control of a heterogeneous group of off-the-shelf miniature RC helicopters. It was developed to complement the theoretical research conducted at IfA. The RCopterX test-bed has been used to rapidly implement and validation theoretical algorithms and system identification techniques of a physical system. There are still a number of challenging problems to be solved for these off-the-shelf helicopters.
In the next steps, we wish to further fuse together cutting edge theoretical work and challenging robotics problems. The main focuses will be: distributed control and localisation of a fleet of micro-quadrocopters, robust proximity measurements and flying in high-turbulence environments. In the world of theoretical work, it is very nice and often useful to have the possibility to demonstrate the application of algorithms.
More information available here


Autonomous Racing

The ORCA (Optimal RC Racing) Project developed (and improves) a test bed consisting of a race track, a infrared camera based tracking system and modified 1:43 dnano RC cars, in order to study control algorithms allowing high-speed, real-time control. On the test bed different fast MPC algorithms are implemented, allowing the cars to online plan their trajectory only based on the track layout and avoid other cars. To allow competitive racing between automatically controlled cars, game theoretical methods are used to derive new control strategies, suited for competitive racing.
More information available here


Type of Seminar:
Public Seminar
Speaker:
organized by the IfA laboratory
Date/Time:
Dec 02, 2014   16:15
Location:

ETF E1
Contact Person:

No downloadable files available.
Biographical Sketch: