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Incremental Updating Multirobot Formation Using Nonlinear Model Predictive Control Method With General Projection Neural Network
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DOI：10.1109/TIE.2018.2864707.png)
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Abstract
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In this paper, an incremental centralized formation system is developed for controlling the multirobot formation with joining robots, and a nonlinear model predictive control (NMPC) method is implemented as the controller. The incremental updating method is used to update the system's state in real time, when there is a new robot joining during the formation process. Then, an NMPC approach is developed to reformulate the formation system into a convex nonlinear minimization problem, which can be further transformed into a quadratic programming (QP) with constraints. Then, a general projection neural network (GPNN) is implemented for solving this QP problem online to get the optimal inputs. In the end, two examples of incremental multirobot formation are demonstrated to verify the effectiveness of this method.
Keywords:
General projection neural network (GPNN)
incremental updating method
multirobot formation control
nonlinear model predictive control (NMPC)
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