Evolutionary algorithms for the multi-objective optimization of stacked dielectric elastomer actuators

Dielectric elastomer stack actuators are a promising configuration of electroactive polymer actuators due to their favourable balance of output force and stroke capabilities. These performance characteristics are highly dependent on many factors including layer geometry, mechanical and electrical material properties, etc. Thus, the specification of an optimal actuator design remains a challenging task. This study aims to assess the relationship of these factors on actuator performance by the application of evolutionary optimization algorithms in conjunction with a coupled multi-physics finite element simulation. This approach rapidly identifies the optimal actuator performance without the computational expense of simulating the entire design space.