Controller Synthesis for Adaptive Optics Systems in Telescopes
- ID: 14124
- Type(s): Projet de semestre MA GM, Projet de Master (PDM) GM
- Section(s): GM
- Status: Complet
- Professor: Alireza Karimi, Vaibhav Gupta
ROJECT SUMMARY
Adaptive optics (AO) systems are critical in overcoming atmospheric distortions in ground-based telescopes, enabling sharper and more detailed astronomical observations. This project focuses on designing and synthesising a robust, real-time controller for an AO system. By leveraging advanced control theory, the project aims to significantly enhance the performance of AO systems, ensuring reliable correction of wavefront distortions and improving the quality of astronomical images.
BACKGROUND AND MOTIVATION
Telescopes observing through Earth’s atmosphere suffer from distortions caused by turbulent air layers, which degrade image resolution. Adaptive optics counteract this by using deformable mirrors and wavefront sensors to correct for distortions in real-time.
Current AO systems, while effective, face limitations in:
* Handling dynamic, unknown atmospheric conditions.
* Scalability for large telescopes and next-generation systems.
By synthesising a controller tailored to these challenges, this project seeks to push the boundaries of AO performance, paving the way for discoveries in astronomy and astrophysics.
OBJECTIVES
1. Design and develop a robust controller that addresses dynamic atmospheric variations.
2. Validate performance through simulation (and hardware) implementation using an AO testbed.
3. Ensure scalability and adaptability of the controller for different telescopes and operational conditions.
REQUIREMENTS
The project demands a solid academic foundation in control courses, particularly in ‘Advanced Control Systems.’ Proficiency in the frequency domain approach and robust control techniques is especially critical.
- Professor(s)
- Alireza Karimi, Vaibhav Gupta
- Administration
- Barbara Marie-Louise Frédérique Schenkel
- External
- Department of Astronomy, UNIGE, Isaac Dinis, [email protected]
- Site
- ddmac.epfl.ch, la.epfl.ch
Data-driven / ML-based control with robust performance for microvibration damping platform
- ID: 14270
- Type(s): Projet de Master (PDM) GM
- Section(s): GM
- Status: Validé
- Professor: Alireza Karimi
The hybrid microvibration damping platform (MIVIDA) developed at CSEM was designed to demonstrate the capabilities of data-driven
control design methods for adaptive disturbance rejection. The modular platform comprises an adjustable number of passive dampers, a
set of proof mass actuators (PMAs) creating a 6 DoF force tensor, and a payload interface capable of accommodating various types of
sensitive instruments. Using the set of actuators and based on the accelerometer measurements close to the payload, the platform
actively rejects disturbances induced to the suspended base plate using an external inertial shaker. At the current stage, the
implemented data-driven control laws need to be recomputed every time a new payload is mounted. The objective of the master project
is to develop a robust performance controller delivering stability and performance for a variety of payloads without requiring retuning of
the system.
Different control design methods shall be studied in the scope of the project. A data-driven uncertainty set can be acquired by
performing system identification experiments for a number of different payloads. A robust controller can be computed based on the
acquired input/output data using convex optimisation. Further possible methods involve machine learning using the input/output time
series as training dataset. As an example, offline reinforcement learning allows to design recurrent neural networks (RNN) or
physics-informed neural networks (PiNN) enabling robustness of the controller for varying system properties which cannot be modelled.
The exact nature and amount of design methods to be studied will be defined during the project.
The student will be working in the Sensing & Control laboratory at CSEM Neuchâtel in the scope of a PdM in industry.
- Professor(s)
- Alireza Karimi
- External
- CSEM Neuchâtel, Elias Klauser, [email protected]
- Site
- https://www.csem.ch/en/tailored-services/microvibration-testing/
Robust controller design and implementation on a 2DoF Gyroscope
- ID: 14229
- Type(s): Projet de semestre MA GM
- Section(s): GM
- Status: Validé
- Professor: Alireza Karimi, Vishnu Varadan
The objective of this project is to design a controller for a nonlinear system, a 2DoF Gyoscope. The nonlinearities in the dynamics will be handled using appropriate methods like feedback linearisation. Uncertainty quantification techniques using data will then be employed to design controllers that robustly stabilise the system with respect to parameter uncertainties and unmodelled nonlinearities. The designed controller should then be validated on the system. Controller implementation and real-time interface would be done through LabVIEW.
- Comment
- Knowledge of courses System Identification and Advanced Control Systems are ideal. Contact Vishnu Varadan ([email protected]) and Vaibhav Gupta ([email protected]) to apply for the project.
- Professor(s)
- Alireza Karimi, Vishnu Varadan
- Administration
- Barbara Marie-Louise Frédérique Schenkel
- Site
- https://www.epfl.ch/labs/la/, https://www.epfl.ch/labs/ddmac/
Robust controller design and implementation on an Active Suspension system
- ID: 14245
- Type(s): Projet de semestre MA GM
- Section(s): GM
- Status: Complet
- Professor: Alireza Karimi, Vishnu Varadan
The objective of this project is to set up an Active Suspension system test bench and apply data-driven robust control techniques on it. Data acquisition and controller implementation would be done using LabVIEW and NI DAQs. The designed controller would be robust to the parametric uncertainties in the system and will be verified and validated on the test bench.
- Professor(s)
- Alireza Karimi, Vishnu Varadan
- Administration
- Barbara Marie-Louise Frédérique Schenkel
- Site
- https://www.epfl.ch/labs/la/, https://www.epfl.ch/labs/ddmac/
Sequential Learning and Control
- ID: 14240
- Type(s): Projet de semestre MA GM
- Section(s): GM
- Status: Validé
- Professor: Alireza Karimi, Zhaoming Qin
This project aims to develop a novel control framework that bridges the gap between offline control and online control. The framework consists of two phases, i.e., experiment design, carried out without immediate performance considerations, and robust controller synthesis to minimize a performance index. As the quality of experimental data directly affects controller performance, the experiment is tailored to facilitate subsequent controller design. The project focuses on mathematically formalizing this pipeline and optimizing its components.
- Professor(s)
- Alireza Karimi, Zhaoming Qin
- Administration
- Barbara Marie-Louise Frédérique Schenkel
Swing up controller of an inverted pendulum using partial feedback linearization
- ID: 14246
- Type(s): Projet de semestre MA GM
- Section(s): GM
- Status: Complet
- Professor: Alireza Karimi, Vishnu Varadan
This project explores the implementation of a partial feedback linearization algorithm for the swing up controller of an inverted pendulum. Collocated and Non-collocated schemes will be explored. The algorithm will also be extended to the data-driven paradigm. The designed controller will be implemented on the hardware setup using MATLAB, Simulink.
- Professor(s)
- Alireza Karimi, Vishnu Varadan
- Administration
- Barbara Marie-Louise Frédérique Schenkel
- Site
- https://www.epfl.ch/labs/la/, https://www.epfl.ch/labs/ddmac/