The subject of this paper is about the use of a suspended Cable-Driven Parallel Robot (CDPR) for pickand-place operations of heavy and heterogeneous objects. The knowledge of the payload mass and its center of mass in realtime is an asset for robust control of the device, which is required to ensure a good stability, especially when the objects have different shapes, sizes and masses. Accordingly, this paper aims at experimentally evaluating the effects of (i) the pulleys modeling and (ii) the use of force sensors for the payload estimation. It turns out that the consideration of the pulleys into the geometric model of the robot improves the mass and center of mass estimations of the payload. A comparison is made between the estimation of cable tensions from force sensors and from motor currents. Finally, a torque controller with a feedforward term for real-time mass compensation is proposed and implemented on a CDPR prototype.
This paper deals with the design of a robust control scheme for a suspended Cable-Driven Parallel Robot (CDPR), composed of eight cables and a moving platform (MP), suitable for pick-and-place operations of heterogeneous objects with different shapes, sizes and masses, up to a total load of 700 kg. Dynamometers measure the force applied by each cable onto the moving-platform and are used to assess the payload mass at any time. In the proposed control solution, each motor of the CDPR is directly driven by a PD torque controller, which takes benefit of the real-time payload estimation in a feedforward term. In order to evaluate its performance, experiments on a typical pick and place trajectory are realized for different payloads. As a result, three control schemes: (i) a Proportional-Derivative (PD) torque controller; (ii) a PD controller with compensation of the MP mass only and (iii) a PD controller with real-time mass estimation and compensation are experimentally compared with respect to their positioning accuracy. It turns out that a good estimation of the payload is obtained in real-time thanks to the dynamometers. Moreover, the higher the payload mass, the more accurate the proposed controller with respect to its two counterparts.
A novel criterion is introduced in this paper to determine the set of cable tensions for Cable-Driven Parallel Robots (CDPRs) with the aim of maximizing the robot stiffness along a specific direction. Based on the feasible polygon of the CDPR and its stiffness matrix, an algorithm selects the set of admissible cable tensions leading to the smallest moving-platform displacement, the moving-platform being subject to an external wrench. The proposed tension distribution is implemented in a control scheme and experimented on a fully-constrained CDPR for a window cleaning application.
A suspended Cable-Driven Parallel Robot (CDPR) composed of eight cables and a moving platform (MP) is used in a pick-and-place application of metal plates with different shapes, sizes and masses. In order to ensure robust control despite mass variation, several combinations of control schemes and control laws have been experimented on a prototype at IRT Jules Verne, France. The main objective of this paper is to provide recommendations on the selection of a control strategy depending on the available information on the carried mass, and the presence or absence of force sensors. Three scenarios are considered representing a degradation of the information on the carried mass to observe the impact on the performance of applicable control strategies. In a first case, force sensors are assumed available to measure cable tension, allowing the real-time estimation of the carried mass. In a second case, the mass of the MP is known, but not the mass of the carried metal plate whereas the third case considers no information at all on both the MP and the carried metal plate. The tested control laws include a standard proportional-derivative controller (PD), and a recently developed nonlinear controller balancing between sliding mode and linear algorithms (SML). The performances of each control strategy are analyzed along a test trajectory for several payloads, and a decision tree is proposed.
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