Distributed Formation Control For Multiple Non-Holonomic Wheeled Mobile Robots With Velocity Constraint By Using Improved Data-Driven Iterative Learning

In this paper, a distributed proportional-integral data-driven iterative learning control (PI-DDILC) algorithm is developed to achieve the formation problem for non-holonomic and velocity constrained wheeled mobile robots (WMRs) under repeatable operation environment. Firstly, the formation problem is transformed into a tracking problem with a certain deviation from the reference trajectory. And a distributed kinematics control algorithm is designed by using leader-follower strategy and graph theory. Then, to solve the problem of unknown dynamic model, the relationship between WMR's output and input is first derived by utilizing the iteration-domain dynamical linearization technique. After that, the improved data-driven iterative learning dynamics control algorithm is provided, which includes both proportional and integral terms along the iteration axis. This algorithm can ensure a group of WMRs to realize formation and only use I/O data of each WMR. Compared with DDILC, PI-DDILC can significantly enhance the response speed and transient performance of WMR system formation. The excellence of the improved algorithm is certified by simulation, and a performance index is designed to quantify the results of the two on formation performance. (C) 2020 Elsevier Inc. All rights reserved.