title: A double-loop structure in the adaptive generalized predictive control algorithm for control of robot end-point contact force.
abstract: Robot force control is an essential issue in robotic intelligence. There is much high uncertainty when robot end-effector contacts with the environment. Because of the environment stiffness effects on the system of the robot end-effector contact with environment, the adaptive generalized predictive control algorithm based on quantitative feedback theory is designed for robot end-point contact force system. The controller of the internal loop is designed on the foundation of QFT to control the uncertainty of the system. An adaptive GPC algorithm is used to design external loop controller to improve the performance and the robustness of the system. Two closed loops used in the design approach realize the system׳s performance and improve the robustness. The simulation results show that the algorithm of the robot end-effector contacting force control system is effective.
authors: Key Lab of Industrial Computer Control Engineering of Hebei Province, Yanshan University, Qinhuangdao 066004, China. Electronic address: wenshuhuan@sohu.com.
authors: Shuhuan
authors: S
authors: Wen
authors: Key Lab of Industrial Computer Control Engineering of Hebei Province, Yanshan University, Qinhuangdao 066004, China.
authors: Jinghai
authors: J
authors: Zhu
authors: Key Lab of Industrial Computer Control Engineering of Hebei Province, Yanshan University, Qinhuangdao 066004, China.
authors: Xiaoli
authors: X
authors: Li
authors: College of Computer Science, Zhejiang University of Technology, Hangzhou 310023, China. Electronic address: sy@ieee.org.
authors: Shengyong
authors: S
authors: Chen
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D005246:Feedback; D008962:Models, Theoretical; D009038:Motion; D017711:Nonlinear Dynamics; D012371:Robotics / Q000379:methods*
keywords: Contact force; Generalized predictive control; Quantitative feedback theory