Stewart Platform (SP) mechanism has wide application area on aerospace and manufacturing industry with its nonlinear structure allowing spatial motion capabilities. However, nonlinearities in the structure of the mechanism lead to complications in the dynamics of the system and result in complex control algorithms for dexterity in motion and force/torque feedback. Therefore, this paper aims to represent stiffness control by means of independent joint fuzzy-PD control algorithm with gain scheduling on an experimental 3 \times 3 SP parallel robotic mechanism to be used as a fly-by-wire flight control unit. Model and real system responses are compared employing stiffness control so that the model is valid for control design trials. Following the selection of optimum control coefficients of self-tuning structure, responses are compared with alternative control algorithms like fuzzy-PD, self-tuning fuzzy PD and PD controllers. Optimum control coefficients are selected minimizing force error integral over a spiral force path on nine chosen points on the workspace. However, torque feedback is applied minimizing the torque error for simple angular motions. System responses for selected controllers are presented and discussed.

Stewart Platform (SP) mechanism has wide application area on aerospace and manufacturing industry with its nonlinear structure allowing spatial motion capabilities. However, nonlinearities in the structure of the mechanism lead to complications in the dynamics of the system and result in complex control algorithms for dexterity in motion and force/torque feedback. Therefore, this paper aims to represent stiffness control by means of independent joint fuzzy-PD control algorithm with gain scheduling on an experimental 3 \times 3 SP parallel robotic mechanism to be used as a fly-by-wire flight control unit. Model and real system responses are compared employing stiffness control so that the model is valid for control design trials. Following the selection of optimum control coefficients of self-tuning structure, responses are compared with alternative control algorithms like fuzzy-PD, self-tuning fuzzy PD and PD controllers. Optimum control coefficients are selected minimizing force error integral over a spiral force path on nine chosen points on the workspace. However, torque feedback is applied minimizing the torque error for simple angular motions. System responses for selected controllers are presented and discussed.