Coordination control of robot manipulators using flat outputs

Published ArticleThis paper focuses on the synchronizing control of multiple interconnected flexible robotic manipulators using differential flatness theory. The flatness theory has the advantage of simplifying trajectory tracking tasks of complex mechanical systems. Using this theory, we propose a new synchronization scheme whereby a formation of flatness based systems can be stabilized using their respective flat outputs. Using the flat outputs, we eliminate the need for cross coupling laws and communication protocols associated with such formations. The problem of robot coordination is reduced to synchronizing the flat outputs between the respective robot manipulators. Furthermore, the selection of the flat output used for the synchronizing control is not restricted as any system variable can be used. The problem of unmeasured states used in the control is also solved by reconstructing the missing states using flatness based interpolation. The proposed control law is less computationally intensive when compared to earlier reported work as integration of the differential equations is not required. Simulations using a formation of single link flexible joint robots are used to validate the proposed synchronizing control

Coordination control of robot manipulators using flat outputs

Published ArticleThis paper focuses on the synchronizing control of multiple interconnected flexible robotic manipulators using differential flatness theory. The flatness theory has the advantage of simplifying trajectory tracking tasks of complex mechanical systems. Using this theory, we propose a new synchronization scheme whereby a formation of flatness based systems can be stabilized using their respective flat outputs. Using the flat outputs, we eliminate the need for cross coupling laws and communication protocols associated with such formations. The problem of robot coordination is reduced to synchronizing the flat outputs between the respective robot manipulators. Furthermore, the selection of the flat output used for the synchronizing control is not restricted as any system variable can be used. The problem of unmeasured states used in the control is also solved by reconstructing the missing states using flatness based interpolation. The proposed control law is less computationally intensive when compared to earlier reported work as integration of the differential equations is not required. Simulations using a formation of single link flexible joint robots are used to validate the proposed synchronizing control

Synchronized control with neuro-agents for leader-follower based multiple robotic manipulators

In this paper, a new neural network enhanced synchronized control approach is proposed for multiple robotic manipulators systems (MRMS) based on the leader-follower network communication topology. The justification of introducing two adaptive Radial Basis Function Neural Networks (RBF NN), also called neuro-agents, is to facilitate the whole control system design and analysis. Otherwise such design is impossible with classical analytical procedure. The first agent is the neuro-compensator to accommodate uncertainty associated with the follower manipulators, and the second agent is the neuro-estimator to obtain acceleration of the leader manipulator. Correspondingly the stability analysis of the designed control system is formulated with Lyapunov method. Finally numerical bench tests under various critical conditions are conducted to validate the effectiveness of the proposed approach. © 2013 Elsevier B.V