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In this work, a position control in task space for slider-crank mechanisms is presented. In order to apply linear controllers it is required to linearize the mechanism dynamics at an equilibrium point. However, complete dynamic knowledge is needed and the linearization technique gives an oversimplified model that affects the control performance. In this work, it is proposed a novel method to design task space controllers without using the complete knowledge of the mechanism dynamics and linearization methods. From the extended dynamic model of parallel robots, it can be seen that the end-effector (slider) dynamics is expressed as a linear system that can be used directly for the control design instead of the complete mechanism linear dynamics. The approach requires a minimal knowledge of the mechanism dynamics and avoids linearization methods. To verify our approach, it is used pole placement and sliding mode controllers whose gains are tuned according to the slider dynamics. A linear sensor is mounted at the slider to measure its position and avoids considering noise and disturbances at links before the slider. Simulations and experiments are presented to validate our approach using two kinds of slider-crank mechanisms.

Task Space Position Control of Slider-Crank Mechanisms Using Simple Tuning Techniques Without Linearization Methods