HYBRID NEURAL LUMPED ELEMENT APPROACH IN INVERSE MODELING OF RF MEMS SWITCHES

RF MEMS switches have been efficiently exploited in various applications in communication systems. As the dimensions of the switch bridge influence the switch behaviour, during the design of a switch it is necessary to perform inverse modeling, i.e. to determine the bridge dimensions to ensure the desired switch characteristics, such as the resonant frequency. In this paper a novel inverse modeling approach based on combination of artificial neural networks and a lumped element circuit model has been considered. This approach allows determination of the bridge fingered part length for the given resonant frequency and the bridge solid part length, generating at the same time values of the elements of the switch lumped element model. Validity of the model is demonstrated by appropriate numerical examples

ARTIFICAL NEURAL NETWORKS IN RF MEMS SWITCH MODELING

The increased growth of the applications of RF MEMS switches in modern communication systems has created an increased need for their accurate and efficient models. Artificial neural networks have appeared as a fast and efficient modeling tool providing similar accuracy as the standard commercial simulation packages. This paper gives an overview of the applications of artificial neural networks in modeling of RF MEMS switches, in particular of the capacitive shunt switches, proposed by the authors of the paper. Models for the most important switch characteristics in electrical and mechanical domains are considered, as well as the inverse models aimed to determine the switch bridge dimensions for given requirements for the switch characteristics

Artificial Neural Network based Design of RF MEMS Capacitive ShuntSwitches

Artificial neural networks (ANNs) have appeared as a very efficient alternative to time consuming full-wave simulations of electrical characteristics of RF MEMS. In this paper, a new ANN based method to be used in the design of RF MEMS devices is proposed. ANNs are trained to model dependence of the scattering parameters and the resonant frequency of an RF MEMS switch on the switch geometrical parameters, as well as to perform the opposite procedure, i.e., to determine values of the geometrical parameters to achieve the desired electrical resonant frequency. The developed models can be used for fast simulation and optimization of the switch characteristics replacing time consuming procedures in full-wave simulators, which leads to a significant reduction of time needed for the device design.9 halama