Automatica, December 2003, Volume 39, No. 12
System identification is a field of systems and control that has delivered powerful methods and tools for system modelling. The current status is that while the linear theory for identification has become very much mature, the challenges for the field are in more complex systems (nonlinear, distributed, hybrid, large scale physical models), in particular goal-oriented modelling issues (identification for control, diagnosis, detection, monitoring etc.), and in high-tech applications. In many application areas the problem of handling large amounts of data in order to extract underlying structural information has become of increasing importance, as e.g. seen in bioinformatics, biotechnology, plant-wide process control and optimization.
The scope of the special issue is to sketch the results and the current challenges in data-based modelling and identification; the contributions are not limited to the ”classical” identification community, but particular identification-related developments in adjacent areas (statistics, signal processing, machine learning, computer science) will be incorporated.
Submission deadline: February 1, 2004
Prospective authors should submit their contribution before February 1, 2004 through the Automatica web-based paper handling system Pampus, available at www.autsubmit.com. Submissions can be either in full paper or brief paper format. Papers for the Special Issue should be submitted as a Special Issue Paper to Special Issue Editor Bo Wahlberg only.