Neural adaptive PID formation control of car-like mobile robots without velocity measurements

A virtual leader-follower formation control of a group of car-like mobile robots is addressed in this paper. First, the kinematic and dynamic models of car-like robots are transformed into a second-order leader-follower formation model which inherits all structural properties of the robot dynamic model. Then, a new observer-based proportional-integral-derivative formation controller is proposed to force that all robots construct a desired formation with respect to a predefined virtual leader. To improve the formation tracking and observation performance, the integral action is incorporated into the design of the observer-controller scheme. Adaptive robust and neural network techniques are also employed to compensate uncertain parameters, unmodeled dynamics, and external disturbances. Lyapunov's direct method is utilized to show that the formation tracking and observation errors are semi-globally uniformly ultimately bounded. Then, the proposed controller is extended to the leader-follower formation of a team of tractor-trailer systems. Finally, simulation results illustrate the efficiency of the proposed controller.