Cooperative Deterministic Learning-Based Formation Control for a Group of Nonlinear Mechanical Systems Under Complete Uncertainty

In this work we address the formation control problem for a group of nonlinear mechanical systems with complete uncertain dynamics under a virtual leader-following framework. We propose a novel cooperative deterministic learning-based adaptive formation control algorithm. This algorithm is designed by utilizing artificial neural networks to simultaneously achieve formation tracking control and locally-accurate identification/learning of the nonlinear uncertain dynamics of the considered group of mechanical systems. To demonstrate the practicality and verify the effectiveness of the proposed results, numerical simulations have been conducted.