Neural-Network-Based Finite-Time Fault-Tolerance Consensus Control of Second-Order Systems Under Channel Fading and Input Quantized
Zijing Li, Kai Zheng, Shuanghe Yu · 2024
In this article, the main focus is finite-time fault-tolerant consensus problem of second-order nonlinear multiagent systems with input quantization and channel fading. By using neural networks to approximate nonlinear terms, more accurate estimation of nonlinear functions can be achieved. Combining sliding mode controller with neural networks to improve the robustness. Combining control theoretical knowledge, a detailed analysis was conducted on the consensus analysis under channel fading and input quantization. Examples and simulation results were provided to verify the effectiveness of theoretical results.