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.

Proportional-Derivative (PD) control is one of the most widely used controllers, especially for robot manipulators. When the robot presents gravitational terms, PD control cannot guarantee position convergence, therefore compensation is required such as PD with gravity compensation, PD+G. PD+G control requires knowledge of the gravitational term and there exist several results that prove global asymptotic stability. However, there is no method to tune the PD gains. In this work, a novel method to tune the PD+G controller is proposed. The tuning method is obtained using the global asymptotic stability result of the La Salle's theorem and robot dynamics properties. A comparison between previous works is realized via simulations and experiments to verify our approach. The results show fast and smooth convergence to the desired reference without overshoots.

This paper presents a synthesis of a spherical parallel manipulator for a shoulder of a seven-degrees-of-freedom prosthetic human arm using a multi-objective optimization. Three design objectives are considered, namely the workspace, the dexterity, and the actuators torques. The parallel manipulator is modelled considering 13 design parameters in an optimization procedure. Due to the non-linearity of the design problem, genetic algorithms are implemented. The outcomes show that a suitable performance of the manipulator is achieved using the proposed optimization.

Deployable mechanisms in CubeSat satellites have many problems with the system that provides the anchor position. The main defect of the traditional deployment mechanisms for solar panels in CubeSats is the lack of position system to block the back-driving of the panel when it reaches the final phase of the deployment. This generates spurious oscillations in the panel, affecting the photovoltaic process as well as generating fatigue in the mechanical elements of the mechanism (hinge or pin). In this work, the design, analysis and manufacture of a deployment mechanism for CubeSat solar panels is shown. A finite element method analysis was carried out in a hinge with an integrated blocking system as well as a double torsion spring, which can be used on CubeSats. The outcome shows the layout of the described anchor hinge and the used double-torsion spring, which provides a positive direction torque transfer. Likewise, the performed numerical analyses on the designed system, reduce the weight and optimise the geometry of the mechanism, showing its feasibility as well as the potential applications and further research in the area.

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