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.