TY - GEN
T1 - Tracking Control of Fully-Constrained Cable-Driven Parallel Robots using Adaptive Dynamic Programming
AU - Li, Shuai
AU - Zanotto, Damiano
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/11
Y1 - 2019/11
N2 - In this paper, a new adaptive tracking controller with learning ability is proposed for fully-constrained cable-driven parallel robots (CDPRs). For these systems, the necessity of maintaining positive and bounded tensions in all cables while coping with disturbances represents a critical control requirement. To achieve this goal, we propose a control law based on adaptive dynamic programming (ADP), with an actorcritic structure. In the critic part, an artificial neural network (NN) approximates the value function which is to evaluate the system performance; in the action part, the controller's parameters are tuned online to achieve optimal control performance. Additionally, the anti-windup (AW) technique is combined with the adaptive controller to cope with the input saturation problem. The stability of the closed-loop system with the proposed control algorithm is proved using the Lyapunov method. Numerical simulations show the effectiveness of the proposed controller.
AB - In this paper, a new adaptive tracking controller with learning ability is proposed for fully-constrained cable-driven parallel robots (CDPRs). For these systems, the necessity of maintaining positive and bounded tensions in all cables while coping with disturbances represents a critical control requirement. To achieve this goal, we propose a control law based on adaptive dynamic programming (ADP), with an actorcritic structure. In the critic part, an artificial neural network (NN) approximates the value function which is to evaluate the system performance; in the action part, the controller's parameters are tuned online to achieve optimal control performance. Additionally, the anti-windup (AW) technique is combined with the adaptive controller to cope with the input saturation problem. The stability of the closed-loop system with the proposed control algorithm is proved using the Lyapunov method. Numerical simulations show the effectiveness of the proposed controller.
KW - adaptive dynamic programming
KW - anti-windup
KW - cable-driven parallel robots
KW - neural networks
KW - tracking control.
UR - http://www.scopus.com/inward/record.url?scp=85081164168&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85081164168&partnerID=8YFLogxK
U2 - 10.1109/IROS40897.2019.8968569
DO - 10.1109/IROS40897.2019.8968569
M3 - Conference contribution
AN - SCOPUS:85081164168
T3 - IEEE International Conference on Intelligent Robots and Systems
SP - 6781
EP - 6787
BT - 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2019
T2 - 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2019
Y2 - 3 November 2019 through 8 November 2019
ER -