Interaction force control of industrial manipulators via neural network-based integral terminal sliding mode control algorithm

• Published in: Nonlinear dynamics Vol. 113; no. 19; pp. 26361 - 26375
• Main Authors: Zong, Like, Jiang, Cuiqing, Du, Haibo, Luo, Yueyue, Cong, Yongzheng
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Nature B.V 01.10.2025
• Subjects: Algorithms; Closed loop systems; Closed loops; Control algorithms; Control systems; Control theory; Controllers; Design; Disturbances; Dynamic characteristics; Feedback control; Friction; Impedance; Industrial robots; Neural networks; Robotics; Robots; Sliding mode control; System theory; Systems theory; Tracking control
• ISSN: 0924-090X; 1573-269X
• DOI: 10.1007/s11071-025-11483-8

For the interaction force control problem of the industrial robots system, a novel impedance-based finite-time disturbance rejection interaction force control algorithm is designed. Firstly, based on the impedance control framework, the interaction force tracking control problem is transformed into a trajectory tracking control problem. Secondly, in the absence of uncertain disturbances, a finite-time trajectory tracking control algorithm is developed using homogeneous system theory and the dynamic properties of the robot system. Then, considering the presence of uncertain disturbances, an online disturbance estimation method is constructed based on an RBF neural network. To address the disturbance estimation residual, an integral terminal sliding mode controller is designed via sliding mode control techniques, guaranteeing finite-time convergence of the closed-loop system. Finally, simulation and experimental results demonstrate the effectiveness of the proposed algorithm.