TY - JOUR
T1 - Finite-time fault-tolerant coordination control for multiple Euler–Lagrange systems in obstacle environments
AU - Zhou, Ning
AU - Xia, Yuanqing
AU - Chen, Riqing
N1 - Publisher Copyright:
© 2017 The Franklin Institute
PY - 2017/5
Y1 - 2017/5
N2 - In obstacle environments, the problem of coordination tracking control for a team of Euler–Lagrange systems is investigated under modeling uncertainties, actuator faults and disturbances. First, syncretizing the Null-Space-based Behavioral (NSB) control, graph theory and finite-time control method, a novel desired velocity is predesigned to achieve the finite-time obstacle avoidance and coordination tracking. Then a set of finite-time fault-tolerant coordination control laws (FFCCLs) are presented to guarantee all of the agents to track a dynamic target while avoiding obstacles/collisions. To improve the robustness and control accuracy of the systems, an adaptive control gain is incorporated into the FFCCL so that the derived algorithm can be implemented without manual parameter adjustment. Both of the control architectures are distributed, model-independent and robust with respect to modeling uncertainties, actuator faults and disturbances. Finally, several numerical simulations are presented to demonstrate the efficacy of the control strategies, showing that the overall motion of the two tasks can be accomplished satisfactorily with high precision.
AB - In obstacle environments, the problem of coordination tracking control for a team of Euler–Lagrange systems is investigated under modeling uncertainties, actuator faults and disturbances. First, syncretizing the Null-Space-based Behavioral (NSB) control, graph theory and finite-time control method, a novel desired velocity is predesigned to achieve the finite-time obstacle avoidance and coordination tracking. Then a set of finite-time fault-tolerant coordination control laws (FFCCLs) are presented to guarantee all of the agents to track a dynamic target while avoiding obstacles/collisions. To improve the robustness and control accuracy of the systems, an adaptive control gain is incorporated into the FFCCL so that the derived algorithm can be implemented without manual parameter adjustment. Both of the control architectures are distributed, model-independent and robust with respect to modeling uncertainties, actuator faults and disturbances. Finally, several numerical simulations are presented to demonstrate the efficacy of the control strategies, showing that the overall motion of the two tasks can be accomplished satisfactorily with high precision.
UR - http://www.scopus.com/inward/record.url?scp=85016831954&partnerID=8YFLogxK
U2 - 10.1016/j.jfranklin.2017.02.018
DO - 10.1016/j.jfranklin.2017.02.018
M3 - Article
AN - SCOPUS:85016831954
SN - 0016-0032
VL - 354
SP - 3405
EP - 3429
JO - Journal of the Franklin Institute
JF - Journal of the Franklin Institute
IS - 8
ER -