Norm Optimal Iterative Learning Control with Auxiliary Optimization: A Switching Approach
Owens, D H, Freeman, C T and Chu, Bing (2013) Norm Optimal Iterative Learning Control with Auxiliary Optimization: A Switching Approach. In, IFAC International Workshop on Adaptation and Learning in Control and Signal Processing 2013, 03 - 05 Jul 2013.
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The paper describes a substantial extension of Norm Optimal Iterative Learning Control (NOILC) that permits tracking of a class of finite dimensional reference signals whilst simultaneously minimizing a quadratic cost function. Motivated by practical problems in automation and control, this enables point-to-point motion tasks to be performed whilst reducing effects such as payload spillage, vibration tendencies and actuator wear. Solutions combine feedforward and feedback actions, and are experimentally tested using a robotic arm.
|Item Type:||Conference or Workshop Item (Paper)|
|Divisions:||Faculty of Physical and Applied Science > Electronics and Computer Science > Comms, Signal Processing & Control
Faculty of Physical and Applied Science > Electronics and Computer Science > EEE
|Date Deposited:||16 Oct 2012 23:29|
|Last Modified:||16 Oct 2012 23:29|
|Contributors:||Owens, D H (Author)
Freeman, C T (Author)
Chu, Bing (Author)
|Date:||3 July 2013|
|Further Information:||Google Scholar|
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
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