Decentralized Neural Network Control for Guaranteed Tracking Error Constraint of a Robot Manipulator

作者：Han Seong Ik; Lee Jang Myung^*

来源：International Journal of Control Automation and Systems, 2015, 13(4): 906-915.

DOI：10.1007/s12555-014-0132-2

• Constrained error variable
• decentralized control
• prescribed performance function
• RBF network
• robot manipulator

In this paper, a new constrained error variable similar to sliding mode surface (SMC) is proposed to ensure a prescribed position tracking performance of a robot manipulator. A decentralized controller using this constrained error variable and a radial basis function network (RBF) is designed. The proposed decentralized and constrained control system ensures a prescribed transient and steady-state time positioning performance of the decentralized manipulator components without violation of the prescribed performance. The effectiveness of the proposed decentralized and robust control scheme was determined by comparing the results of simulated and experimental evaluation with the conventional SMC and finite-time terminal SMC methods.

• 出版日期2015-8