Semi-parametric Decentralised Adaptive Control of Discrete-time Nonlinear Multi-agent Systems
Shan Li, Hongbin Ma, Xin Wang, Zhuang Li · 2018
This paper investigates the challenging and significant problem of semi-parametric decentralised adaptive control in discrete-time nonlinear multi-agent systems, where parametric uncertainties and non-parametric uncertainties coexist. To deal with these two kinds of uncertainties, we introduce an auxiliary state to compensate non-parametric uncertainties. Then, we utilize a novel deadzone with threshold converging to zero to guarantee the boundedness of the estimated values of unknown parameters. Based on the certainty equivalence principle, semi-parametric decentralised adaptive controllers are designed to make sure that all agents track the reference state, and the closed-loop system achieves consensus tracking under the condition of strong couplings. Finally, the effectiveness of designed controllers is revealed through numerical simulation.