Nonlinear Model Predictive Formation Control: An Iterative Weighted Tuning Approach

Abstract

A nonlinear model predictive formation controller (NMPFC) was used to converge a group of middle sized mobile soccer robots towards a desired target using the concept of active target tracking. This paper presents a novel approach on the formation controller's weight tuning in order to minimize an objective function that reflects the controller's efficiency with respect to a given criteria. This method is here called Iterative Weight Tuning (IWT). In this paper the effectiveness from the proposed method is shown by the results of simulations and experiment with real robots, compared to the tuning performed using genetic algorithms approach. The results demonstrated that the IWT method was successful in achieving a better set of weights that influenced the formation controller to converge the robots into formation in a better fashion regarding the agents' objective function.