TY - GEN
T1 - Distributed Neural Network Fixed-Time Consensus Control for Multiple Manipulators System with Input Deadzone
AU - Zhan, Haoran
AU - Cao, Yuanchao
AU - Chen, Xin
AU - Chao, Tao
AU - Zhang, Jiyu
AU - Guo, Qing
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - The multiple manipulator system (MMS) has strong coupling properties and nonlinearities, which is used to accomplish complex cooperation tasks. In this study, a distributed consensus control algorithm is presented for indefinite MMS with input deadzone under a directed communication graph.To solve the problem of the network congestion exists in MMS, an event-triggered mechanism (ETM) is proposed to decrease the upgrade rates of output control signal. Furthermore, a RBFNNs is presented to estimate uncertain dynamics for controller compensation. Moreover, by applying backstepping method, a fixed-time controller is developed to ensure that the state errors can convergence to zero point in finite time not relevant to system initial state. Ultimately, the designed control strategy is validated by adequate simulation and experimental results.
AB - The multiple manipulator system (MMS) has strong coupling properties and nonlinearities, which is used to accomplish complex cooperation tasks. In this study, a distributed consensus control algorithm is presented for indefinite MMS with input deadzone under a directed communication graph.To solve the problem of the network congestion exists in MMS, an event-triggered mechanism (ETM) is proposed to decrease the upgrade rates of output control signal. Furthermore, a RBFNNs is presented to estimate uncertain dynamics for controller compensation. Moreover, by applying backstepping method, a fixed-time controller is developed to ensure that the state errors can convergence to zero point in finite time not relevant to system initial state. Ultimately, the designed control strategy is validated by adequate simulation and experimental results.
KW - distributed control
KW - fixed-time consensus
KW - input deadzone
KW - multiple manipulators system
KW - neural network
UR - https://www.scopus.com/pages/publications/105038335539
U2 - 10.1109/CSIS-IAC65538.2025.11161807
DO - 10.1109/CSIS-IAC65538.2025.11161807
M3 - 会议稿件
AN - SCOPUS:105038335539
T3 - 2025 International Annual Conference on Complex Systems and Intelligent Science, CSIS-IAC 2025
SP - 418
EP - 425
BT - 2025 International Annual Conference on Complex Systems and Intelligent Science, CSIS-IAC 2025
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2025 International Annual Conference on Complex Systems and Intelligent Science, CSIS-IAC 2025
Y2 - 16 May 2025 through 18 May 2025
ER -