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Cooperative Adaptive Learning Control for a Group of Nonholonomic UGVs by Output Feedback
[chapter]
2020
Multi Agent Systems - Strategies and Applications
A high-gain observer-based cooperative deterministic learning (CDL) control algorithm is proposed in this chapter for a group of identical unicycle-type unmanned ground vehicles (UGVs) to track over desired reference trajectories. For the vehicle states, the positions of the vehicles can be measured, while the velocities are estimated using the high-gain observer. For the trajectory tracking controller, the radial basis function (RBF) neural network (NN) is used to online estimate the unknown
doi:10.5772/intechopen.87038
fatcat:a6k5rnebavazvfvyuoai2humwu