On the multiobjective optimization of conjugated polymer based trilayer actuators

The main focus of this study is the multiobjective 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 behaviors such as their generated tip displacement and blocking force is of crucial importance. The optimization process leads to exploit the full potentials of these trilayer actuators, and more significantly, increase their performance predictability. Considering mechanical and chemical characteristics of the bending actuators, two mathematical models are developed to capture their performance in terms of tip blocking force and vertical displacement. Results obtained from both models explicitly indicate the trade-off between the two designated outputs. The optimization models include a system of nonlinear equations along with their corresponding constraints. A multiobjective genetic algorithm and a nonlinear programming solver in MATLAB were employed to solve the mathematical models. Ultimately, the results obtained from the two developed optimization methodologies were experimentally verified. For this purpose, a trilayer PPy based actuator was fabricated and related measurements were performed.