An insight how bio-economically optimised resource and energy cycles help in the production of sustainable food can be found here.
Prof. Dr.-Ing. Johann Reger (TU Ilmenau) will give a talk on Exact Backstepping Control for Systems in Pure Feedback Form at 5:30 pm in 2/W014. Everybody is heartily invited. An overview over all past and future seminars can be found here.
Starting in 2019, several members of the ACSD lab will be working on Control of closed energy and mass flow of a high complex production system. The lab will closely collaborate with several industrial and academic partners. Further information can be found here, here and here. An overview over our projects can be found here
The ACSD Lab presents two papers on the Conference on Decision and Control (CDC), which takes place in Nice on December 11th-13th. Dr. Osinenko presents two papers, namely Adaptive Dynamic Programming Using Lyapunov Function Constraints (Göhrt, Osinenko, Streif) and Model Predictive Control with Stage Cost Shaping Inspired by Reinforcement Learning (Beckenbach, Osinenko, Streif). Furthermore, Prof. Streif is co-chair of the Optimal Control V session.
Prof. Streif gives a view in his work as the Dean of the faculty in TUCtalk. The interview (in german) can be watched here.
Victor Magron (CNRS-LAAS,Équipe MAC) will give a talk on Semidefinite programming and moment/sums-of-squares hierarchy for solving polynomial optimization problems at 3:00 pm in 2/W040. Everybody is heartily invited. An overview over all past and future seminars can be found here.
The lab organizes an open invited track on the IFAC World Congress 2020 in Berlin. The topic of the track is Uncertainty Quantification in Control and Optimization - Tools, Methods and Applications. Further details (scope, submission details, other organizers, etc.) can be found here and on the IFAC WC 2020 Website.
The ACSD Lab will present a paper at the IFAC Symposium on Nonlinear Control Systems (NOLCOS) 2019 to be held in Vienna on September 4th-6th. New research results in the area of adaptive dynamic programming will be presented.
Our ACSD lab is part of the new research project "Aufbau eines universitätsweiten Kooperationsnetzwerks Künstliche Intelligenz am Beispiel Ambient Assisted Living" (KIN-TUC). The aim of the group is it, to mitigate the consequences of ageing through artificial intelligence. More information can be found here.
Constructive analysis of eigenvalue problems in control under numerical uncertainty
International Journal of Control, Automation and Systems, 2019
Design and Validation of a Low Cost Programmable Controlled Environment for Study and Production of Plants, Mushroom, and Insect Larvae
Applied Sciences, 2019 [DOI]
Converse optimality for discrete-time systems
IEEE Transactions on Automatic Control, 2019 [DOI]
Adaptive dynamic programming using Lyapunov function constraints
IEEE Control Systems Letters, 2019 [DOI]
Adaptive actor-critic structure for parametrized controllers
11th IFAC Symposium on Nonlinear Control Systems, 2019
Model predictive control with stage cost shaping inspired by reinforcement learning
Proc. Conference on Decision and Control (CDC), 2019
Practical stability analysis of sliding-mode control with explicit computation of sampling time
Asian Journal of Control, 2019 [DOI]
Response to IL-6 trans- and IL-6 classic signalling is determined by the ratio of the IL-6 receptor α to gp130 expression: fusing experimental insights and dynamic modelling
Cell Communication and Signaling, 2019 [DOI]
A Multirate Hierarchical MPC Scheme for Ensemble Systems
Proc. Conference on Decision and Control (CDC), 2018 [DOI]
Hierarchical Control with Guaranteed Fault Diagnosability
Proc. 10th IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS), 2018 [DOI]