Dual-space adaptive synchronization control of redundantly-actuated cable-driven parallel robots

This paper investigates the issue of designing decentralized control laws to cooperatively command a team of general fully actuated manipulators. The purpose is to synchronize their movements while tracking a common desired trajectory. Based on the well-known consensus algorithm, the control strategy consists in synchronizing the joint position and the velocity of each robot in the network with respect to neighboring robots' joints and velocities. Modeled by an undirected graph, the cooperative robot network requires just local neighbor-to-neighbor information exchange between manipulators. So, it does not assume the existence of an explicit leader in the team. Based above all on combination of Lyapunov direct method and cross-coupling strategy, the proposed decentralized control law is extended to an adaptive synchronization control taking into account parameter uncertainties. To address the time delay problems in the network communication channels, the suggested synchronization control law robustly synchronizes robots to track a given trajectory. To this end, Krasovskii functional method has been used to deal with the delay-dependent stability problem. A real-time software simulator is developed to visualize the robot manipulators coordination.

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Optimizing the Torque Distribution of a Redundantly Actuated Parallel Robot to Study the Temporomandibular Reaction Forces During Food Chewing

Journal of Mechanisms and Robotics ◽

10.1115/1.4046651 ◽

2020 ◽

Vol 12 (5) ◽

Author(s):

Naser Mostashiri ◽

Jaspreet Dhupia ◽

Alexander Verl ◽

John Bronlund ◽

Weiliang Xu

Keyword(s):

Inverse Dynamics ◽

Parallel Robot ◽

Parallel Robots ◽

Cost Functions ◽

Measurement Tool ◽

Redundancy Resolution ◽

Theoretical Formulation ◽

Temporomandibular Joints ◽

Redundantly Actuated

Abstract Inverse dynamics solution of redundantly actuated parallel robots (RAPRs) requires redundancy resolution methods. In this paper, the Lagrange’s equations of the second kind are used to derive governing equations of a chewing RAPR. Jacobian analysis of the RAPR is presented. As redundancy resolutions, two different optimization cost functions corresponding to specific neuromuscular objectives, which are minimization of effort of the muscles of mastication and temporomandibular joints (TMJs) loads, are used to find the RAPR’s optimized actuation torque distributions. The actuation torques under the influence of experimentally determined dynamic chewing forces on molar teeth reproduced from a separate chewing experiment are calculated for realistic in vitro simulation of typical human chewing. These actuation torques are applied to the RAPR with a distributed-computed-torque proportional-derivative control scheme, allowing the RAPR’s mandible to follow a human subject’s chewing trajectory. TMJs loads are measured by force sensors, which are comparable with the computed loads from theoretical formulation. The TMJs loads for the two optimization cost functions are measured while the RAPR is chewing 3 g of peanuts on its left molars. Maximum and mean of the recorded loads on the left TMJ were higher in both cases. Moreover, the maximum and mean of the recorded loads on both TMJs were smaller for the cost function minimizing the TMJs loads. These results demonstrate validity of the model, suggesting the RAPR as a potential TMJ loads measurement tool to study the chewing characteristics of patients suffering from pain in TMJs.

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