Semi-global robust tracking consensus for multi-agent uncertain systems with input saturation via metamorphic low-gain feedback

• Autores: Baohui Wang, Weisheng Chen, Bin Zhang
• Localización: Automatica: A journal of IFAC the International Federation of Automatic Control, ISSN 0005-1098, Nº. 103, 2019, págs. 363-373
• Idioma: inglés
• Texto completo no disponible (Saber más ...)
• Resumen

  • This paper proposes a metamorphic adaptive low-gain feedback approach to investigate the semi-global robust tracking consensus problem of multi-agent uncertain systems with input saturation under a directed communication topology. The main contribution is to develop a new robust tracking consensus low-gain feedback algorithm, in which the feedback gain design does not rely on eigenstructure assignment algorithm and the solution of a parametric Algebraic Riccati Equation (ARE). By introducing appropriate assumptions, a class of metamorphic adaptive low-gain feedback protocols is designed based on the limited states information among neighbors. It is proved, in the sense of Lyapunov, that the robust tracking consensus problem for closed-loop multi-agent uncertain systems with input saturation and directed communication topology can be solved. Furthermore, the results are extended to the semi-global robust tracking consensus problem of nonlinear multi-agent uncertain systems with nonlinear input saturation under a jointly connected directed communication topology. Finally, two examples are presented to demonstrate the effectiveness of the proposed theories. ,