Asymptotically consensus tracking control of connected Lagrangian systems with input quantization
Chaoli Wang, Yu Li · 2020
This paper studies the leader-following consensus problem for a class of connected Lagrangian systems, which include input quantization, time-varying control gain and unknown bounded external disturbance under undirected communication topology. Because it is usually not easy to correctly measure the upper bounds of time-varying control gain, nor to measure bounded external disturbance, the upper bounds are considered unknown in this paper. In the undirected communication graph case, the bound of the leader's trajectory can be estimated by a group of observers for each agent. Then, based on the new technique of two-step adaptive distributed control, the tracking errors can asymptotically converge to zero. Moreover, the nonlinearities of the input quantization and the time-varying control gain can be compensated by a carefully selected smooth control protocol. It is shown that all the closed-loop signals are uniformly bounded, and a practical example simulation is given to demonstrate the effectiveness of the proposed scheme.