Multiobjective Optimization of Trilayer Polypyrrole Conducting Polymer Actuators

The main focus of this study is the optimization of a trilayer actuator comprising two layers of polypyrrole and a PVDF membrane core. Since the performance of these actuators is difficult to predict due to their mechanical and chemical properties, optimizing their output behavior such as the tip displacement and blocking force is of crucial importance for utilizing their full potentials and more significantly increasing predictability in their performance. For this purpose, two optimization techniques (multiobjective genetic algorithm and active set algorithm) have been carried out based on a developed mathematical model. Two nonlinear constrained equations representing the tip displacement and the blocking force are formulated and solved for a predetermined thickness of the PVDF core membrane. Both equations are subjected to a bound constraint and a nonlinear equality constraint. The output blocking force and the tip deformation act in a reverse manner and there is a trade-off between them. Accordingly, the results imply that there is no single solution to the problem and a range for each of the design variables should be determined so that there will be a sense of balance between the two objectives. Furthermore, the results obtained from the multiobjective optimization methodology have been verified experimentally.