Optimum sensor selection in control system design is often a non-trivial task to do. This paper presents a systematic design framework for selecting the sensors in an optimum manner that simultaneously satisfies complex system performance requirements such as optimum performance and robustness to structured uncertainties. The framework combines modern control design methods, Monte Carlo techniques and genetic algorithms. Without losing generality its efficacy is tested on an electromagnetic suspension system via appropriate realistic simulations.
|Number of pages||6|
|Journal||IFAC Proceedings Volumes (IFAC-PapersOnline)|
|Publication status||Published - Jan 2011|
|Event||18th World Congress: The International Federation of Automatic Control - Milano, Italy|
Duration: 28 Aug 2011 → 2 Sep 2011
Conference number: 18