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This article investigates the effect of three uncertain parameters on a model of conjugated polymer actuators. These uncertain parameters are the diffusion coefficient (D), the resistance (R), and the double-layer thickness (δ). The model sensitivity to these parameters is analyzed and a parameter estimation study is performed using artificially generated data as well as laboratory yielded experimental measurements. The parameter estimation method used in this article is based on a Bayesian cost function, and gives us an insight on how much the estimation can be trusted, which is useful information for the design of controllers. Results indicate that for stochastic controllers to be designed effectively using this model, the resistance is the best known parameter and should therefore be designed for with greater confidence in its value, while the controller should be more robust with respect to the diffusion coefficient and the double-layer thickness. However, significant discrepancies between the model and its reduced form used for control purposes seem to indicate that a better suited model would be needed to start developing stochastic controllers.

This article investigates the effect of two uncertain parameters on a recent new model of conjugated polymer actuators. These uncertain parameters are the diffusion coefficient (D) and the double-layer capacitance (Cdl), which are difficult to measure directly. The model sensitivity to these parameters is analysed and a parameter estimation study is performed using artificially generated data. The parameter estimation method used in this article is based on a Bayesian cost function, and gives us an insight on how much the estimation can be trusted, which is useful information for the design of controllers. Results indicate that for controllers to be designed effectively using this model, the double-layer capacitance is the best known parameter and should therefore be designed for with greater confidence in its value, while the controller should be much more robust with respect to the diffusion coefficient, which should be treated as a stochastic variable for a certain range of possible values.

This paper presents the effect of three uncertain parameters on a recent model of conjugated polymer actuators and implements a robust controller based on the model developed for this actuator. These uncertain parameters are the diffusion coefficient (D), the charge capacitance (C d ) and the charge-to-strain ratio (α), which are difficult to measure directly. The parameter estimation method used in this article is based on a Bayesian cost function, and gives us an insight on how much the estimation can be trusted, which is useful information for the design of controllers. Results indicate that the charge capacitance is the best known parameter and should therefore be designed for with greater confidence in its value, while the controller should be much more robust with respect to the diffusion coefficient and the charge-to-strain ratio. Based on this finding, a robust controller based on the quantitative feedback theory is implemented and compared with a conventional PID controller. This results in an improvement of the control performance.