Neuro-Genetic Optimization of ElectroThermal Microactuator

Microcantilevers are the basic and fundamental structures used in microsystems for both sensing and actuating applications. In this paper, modeling, simulation and optimization details of a microcantilever based thermal actuator is presented. The advantage of this actuator is, the tip of this actuator which actually drives some other object doesn't get heated and hence can be used in any environment safely. The main objective of this work is to investigate the nature of deflection of microcantilever based actuator for the applied potential difference across the base pads and to find the optimized dimensions for maximum displacement. In this device, two microcantilevers of different dimensions are considered and when these are subjected to same current, deflect differently. This turns the microstructure into a thermal actuator. Then Genetic Algorithm (GA) optimization technique along with ANN is used for finding optimum length of shorter arm of electrothermal actuator for maximum deflection and minimum applied voltage. An ANN simulator is used to generate the deflections for various values of applied voltages and the short arm lengths further the optimal values are found using a Genetic Algorithm using newly derived chromosome representation and crossover operators. This neuro-genetic optimization is realized using MATLAB.