Distributed Adaptive Nonlinear Control with Fusion Least-Squares
Ying Wang, Wuquan Li, Ji‐Feng Zhang · SIAM Journal on Control and Optimization · 2022
This paper is concerned with the adaptive consensus tracking control problem for strict-feedback nonlinear multiagent systems with parameter uncertainty under both fixed and switching topologies. When the topology is fixed, we first propose a novel distributed fusion least-squares algorithm without regressor filtering, which has a clear advantage that the estimate of each agent converges to the true parameter value under a weak cooperative persistent excitation condition. Then, we design a new adaptive consensus tracking control law to guarantee that each agent can asymptotically track the reference trajectory. After that, we generalize the corresponding results to the switching topology case. Finally, two examples are given to demonstrate the theoretical results.