Conjugated polymer actuators can be employed to achieve micro and nano scale precision, and have a wide range of applications including biomimetic robots, and biomedical devices. In comparison to robotic joints, they do not have friction or backlash, but on the other ha
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Conjugated polymer actuators can be employed to achieve micro and nano scale precision, and have a wide range of applications including biomimetic robots, and biomedical devices. In comparison to robotic joints, they do not have friction or backlash, but on the other hand, they have complicated electro-chemo-mechanical dynamics which makes modelling and control of the actuator really difficult. Besides the positive characteristics of these actuators, they have some disadvantages such as creep, hysteresis, highly uncertain and time-varying dynamics. This paper consists of two major parts. In the first part the Takagi–Sugeno (T–S) Fuzzy model is used to represent the uncertain dynamic of the actuator, and the resulted Fuzzy model will be validated using experimental data. In the second part a proportional-derivative fuzzy controller is designed to control the highly uncertain dynamic of conjugated polymer actuator. In order to optimize the performance of fuzzy controller, Genetic Algorithm (GA) is used for tuning the output membership functions. The obtained results show that the designed controller can achieve good performance despite the existence of uncertain actuator dynamics and also it has a better performance than conventional PID controller.
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