LCCMS 2013 - ASCC Special Session on Learning Controllers for Complex Mechatronic Systems
Date2013-06-23 - 2013-06-26
Deadline2013-01-15
VenueIstanbul, Turkey
Keywords
Websitehttps://www.ascc.boun.edu.tr
Topics/Call fo Papers
ASCC 2013 special session on learning controllers for complex mechatronic systems, part of the 2013 IEEE Asian Control Conference (IEEE ASCC 2013), Istanbul, Turkey, June 23-26, 2013.
AIM AND SCOPE
In many practical mechatronic systems, the optimal machine settings are not applied, which can lead to a strong performance loss. One reason for this suboptimal control is that the optimal settings strongly depend on the process parameters and the environmental conditions, which are mostly only known within bounds and which can change drastically over time (e.g. changing temperature, different produced materials, etc.). Another reason for suboptimal performance of mechatronic system is the complex structure of these systems, which often consist of several interacting mechatronic subsystems, where each subsystem has its own characteristics. When there is a strong mutual interaction between different processes on a production machine, it is a complicated task for the machine operators to select the correct settings for all the subsystems to get an optimal global performance. The introduction of learning in the controllers of complex mechatronic systems can significantly enhance
the performance of these systems. The objective of this special session is to share novel ideas on the use of learning controllers in complex mechatronic systems, including both model-based and model-free approaches.
We solicit original submissions describing applications of all flavors of learning control in mechatronic systems. Topics of interest include, but are not limited to, the application of:
* (Approximate) Dynamic Programming
* Reinforcement learning
* Model-based learning controllers
* Model free control approaches
* Learning the interactions between the subsystems in a complex mechatronic system
* Distributed control
IMPORTANT DATES
Submission deadline: Jan 15, 2013
Acceptance notification: Feb 15, 2013
Final version submission: March 15, 2013
Conference: June 23-26, 2013
SUBMISSION INSTRUCTIONS
Please check the main ASCC site for detailed submission instructions:
http://www.ascc.boun.edu.tr/
Special session papers must be submitted with the submission type "Invited Session Paper" with the correct session code: 7XXiaR
ORGANIZERS
Wouter Saeys, KU Leuven, Belgium
Erdal Kayacan, KU Leuven, Belgium
Peter Vrancx , Vrije Universiteit Brussel, Belgium
AIM AND SCOPE
In many practical mechatronic systems, the optimal machine settings are not applied, which can lead to a strong performance loss. One reason for this suboptimal control is that the optimal settings strongly depend on the process parameters and the environmental conditions, which are mostly only known within bounds and which can change drastically over time (e.g. changing temperature, different produced materials, etc.). Another reason for suboptimal performance of mechatronic system is the complex structure of these systems, which often consist of several interacting mechatronic subsystems, where each subsystem has its own characteristics. When there is a strong mutual interaction between different processes on a production machine, it is a complicated task for the machine operators to select the correct settings for all the subsystems to get an optimal global performance. The introduction of learning in the controllers of complex mechatronic systems can significantly enhance
the performance of these systems. The objective of this special session is to share novel ideas on the use of learning controllers in complex mechatronic systems, including both model-based and model-free approaches.
We solicit original submissions describing applications of all flavors of learning control in mechatronic systems. Topics of interest include, but are not limited to, the application of:
* (Approximate) Dynamic Programming
* Reinforcement learning
* Model-based learning controllers
* Model free control approaches
* Learning the interactions between the subsystems in a complex mechatronic system
* Distributed control
IMPORTANT DATES
Submission deadline: Jan 15, 2013
Acceptance notification: Feb 15, 2013
Final version submission: March 15, 2013
Conference: June 23-26, 2013
SUBMISSION INSTRUCTIONS
Please check the main ASCC site for detailed submission instructions:
http://www.ascc.boun.edu.tr/
Special session papers must be submitted with the submission type "Invited Session Paper" with the correct session code: 7XXiaR
ORGANIZERS
Wouter Saeys, KU Leuven, Belgium
Erdal Kayacan, KU Leuven, Belgium
Peter Vrancx , Vrije Universiteit Brussel, Belgium
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Last modified: 2012-12-23 14:39:12