Prescribed performance adaptive event-triggered consensus control for multiagent systems with input saturation

Front Neurorobot. 2023 Jan 19:16:1103462. doi: 10.3389/fnbot.2022.1103462. eCollection 2022.

Abstract

In this paper, a prescribed performance adaptive event-triggered consensus control method is developed for a class of multiagent systems with the consideration of input dead zone and saturation. In practical engineering applications, systems are inevitably suffered from input saturation. In addition, input dead zone is widely existing. As the larger signal is limited and the smaller signal is difficult to effectively operate, system efficacious input encounters unknown magnitude limitations, which seriously impact system control performance and even lead to system instability. Furthermore, when constrained multiagent systems are required to converge quickly, the followers would achieve it with drastic and quick variation of states, which may violate the constraints and even cause security problems. To address those problems, an adaptive event-triggered consensus control is proposed. By constructing the transform function and the barrier Lyapunov function, while state constrained is guaranteed, multiagent systems quickly converge with prescribed performance. Finally, some examples are adopted to confirm the effectiveness of the proposed control method.

Keywords: event-triggered strategy; input dead-zone; input saturation; multiagent systems; prescribed performance; prescribed time.

Grants and funding

This work was funded in part by the National Natural Science Foundation of China under grant 62103115, the Natural Science Foundation of Guangdong Province under grant 2021A1515011636, the Science and Technology Research Program of Guangzhou under grant 202102020975, the Basic and Applied Basic Research Projects jointly funded by Guangzhou and schools (colleges) under grant 202201020233, the Guangzhou Yangcheng Scholars Research Project under grant 202235199, the Special Funds for the Cultivation of Guangdong College Students' Scientific and Technological Innovation (Climbing Program Special Funds.) under grant pdjh2022a0404, and the College Students' Innovative Entrepreneurial Training Plan Program under grant 202211078101.