Kinematic Control of Redundant Manipulators Using Neural Networks

• Published in: IEEE transaction on neural networks and learning systems Vol. 28; no. 10; pp. 2243 - 2254
• Main Authors: Li, Shuai, Zhang, Yunong, Jin, Long
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.10.2017; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Computer simulation; Control stability; Control systems; Kinematic control; Kinematics; Manipulator dynamics; Manipulators; Mathematical model; Model accuracy; Motion control; neural network; Neural networks; nonconvex set; Parallel processing; Position errors; Recurrent neural networks; recurrent neural networks (RNNs); Redundancy; redundant manipulator; Reference signals; robot arm; Robot arms; Robot control; Stability analysis; Theoretical analysis; Tracking control

Redundancy resolution is a critical problem in the control of robotic manipulators. Recurrent neural networks (RNNs), as inherently parallel processing models for time-sequence processing, are potentially applicable for the motion control of manipulators. However, the development of neural models fo...