2134/9258
Konstantinos Michail
Konstantinos
Michail
Argyrios C. Zolotas
Argyrios C.
Zolotas
Roger Goodall
Roger
Goodall
Simulation-based optimum sensor selection design for an uncertain EMS system via Monte-Carlo technique
Loughborough University
2012
Optimum sensor selection
Modern control design
EMS systems
Monte Carlo
Genetic algorithms
Mechanical Engineering not elsewhere classified
2012-01-10 14:54:56
Conference contribution
https://repository.lboro.ac.uk/articles/conference_contribution/Simulation-based_optimum_sensor_selection_design_for_an_uncertain_EMS_system_via_Monte-Carlo_technique/9556400
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.