Distributed formation control for multiple non-holonomic wheeled mobile robots with velocity constraint by using improved data-driven iterative learning. (English) Zbl 1508.70010
Summary: 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.
MSC:
| 70E60 | Robot dynamics and control of rigid bodies |
| 70F25 | Nonholonomic systems related to the dynamics of a system of particles |
| 93A15 | Large-scale systems |
| 93B47 | Iterative learning control |
| 93C85 | Automated systems (robots, etc.) in control theory |
Keywords:
formation control; nonholonomic wheeled mobile robots; data-driven control; iterative learning control; velocity constraint; graph theoryReferences:
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