State-constrained bipartite tracking of interconnected robotic systems via hierarchical prescribed-performance control

This paper investigates the collaborative design problem aiming to achieve state-constrained bipartite tracking of interconnected robotic systems (IRSs) with prescribed performance. In practical applications, physical limitations robots are inevitable. Besides, it is difficult ensure that target trajectory known for each robot IRSs in advance. Thus, important follow and meanwhile obey state constraint being generated from external environment IRSs. To this end, we propose a new hierarchical estimator-based control framework characteristics low computation complexity high task adaptability. With limited accessibility trajectory, newly present estimator observe at time interval through interconnections among robots. The never violated throughout convergence process by using presented algorithm. theoretical proof simulation results validate feasibility framework.