Neural network-based task-space bipartite region reaching control for heterogeneous networked Euler-Lagrange systems
摘要
This paper primarily focuses on the distribu-ted bipartite region reaching control problem for heterogeneous networked Euler-Lagrange systems (NELSs) under directed graphs. A reference velocity observer with the kinematic transformation from the configuration space to the task-space is suitably introduced to design a distributed control scheme by making the best use of its redundant property. The neural network (NN) integrated with robust control technique is then effectively utilized to deal with system model uncertainty and external disturbances. Furthermore, two independent bipartite region reaching algorithms for heterogeneous NELSs are analytically derived for the static and moving region cases based on the Lyapunov stability framework on region potential function. Finally, numerical simulations are provided to verify the cooperative performance of the proposed bipartite region reaching control schemes, including stability, adaptability, and robustness.