A Novel Adaptive Predefined-Time Fuzzy Consensus Control of High-Power Nonlinear Multi-Agent Systems with Input Quantization
Chuhan Zhou, Ying Wang · 2022 41st Chinese Control Conference (CCC) · 2022
This paper investigates the problem of predefined-time fuzzy logic systems (FLS) based consensus control technique for a large family of high-power non-strict-feedback nonlinear systems with input quantization. A novel controller design processing is constructed to guarantee the tracking error converges to a very small interval within the user-predefined time. What's more, the fuzzy approximators are used to handle with the unknown sections of the system. Besides, the problem of input quantization is solved by introducing a separate lemma which converts the quantized input into a “linear-like” form. All the close-loop signals of each agent remain bounded, while the tracking error converges to a very low level eventually. Ultimately, a numerical example proves the effectiveness of the proposed method.