In this paper, a combined kinematic/torque control law is developed for leader-follower based formation control using backstepping in order to accommodate the dynamics of the robots and the formation in contrast with kinematic-based formation controllers that are widely reported in the literature. A multilayer neural network (NN) is introduced along with robust integral of the sign of the error (RISE) feedback to approximate the dynamics of the follower as well as its leader using online weight tuning. It is shown using Lyapunov theory that the errors for the entire formation are asymptotically stable and the NN weights are bounded as opposed to uniformly ultimately bounded (UUB) stability which is typical with most NN controllers. Simulation results are included.
J. Sarangapani and T. A. Dierks, "Asymptotic Stability of Nonholonomic Mobile Robot Formations Using Multilayer Neural Networks," Proceedings of the 46th IEEE Conference on Decision and Control (2007, New Orleans, LA), Institute of Electrical and Electronics Engineers (IEEE), Jan 2007.
The definitive version is available at https://doi.org/10.1109/CDC.2007.4434811
46th IEEE Conference on Decision and Control (2007: Dec. 10-11, New Orleans, LA)
Electrical and Computer Engineering
United States. Department of Education
Keywords and Phrases
Asymptotic Stability; Formation Control; Kinematic/Dynamic Controlle; Lyapunov Methods; Multi-Robot Systems; Neural Network; Neurocontrollers; RISE
Article - Conference proceedings
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