학술논문

NN-Based Bipartite Hysteretic Quantized Control for Stochastic MASs with Unknown Nonlinearity
Document Type
Conference
Source
2023 35th Chinese Control and Decision Conference (CCDC) Control and Decision Conference (CCDC), 2023 35th Chinese. :5291-5296 May, 2023
Subject
General Topics for Engineers
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Protocols
Quantization (signal)
Network topology
Stochastic systems
Simulation
Topology
Nonlinear systems
Neural Network
Hysteresis Quantization
Bipartite Control
Consensus
Language
ISSN
1948-9447
Abstract
This paper mainly studies the bipartite consensus control of second-order stochastic nonlinear multi-agent systems with sensor faults and Prandtl-Ishlinskii hysteresis. The objective of this issue is to design a control protocol with quantitatively adaptive to deal with unknown nonlinearity in systems. A novel distributed control technique that does not need forecasting the lowest limits of the asymmetric hysteresis quantizer and unknown hysteresis has been provided using the adaptive compensation technique. In addition, this technique has been presented to address the issue caused by sensor faults, and the stochastic Lyapunov stability theorem is used to verify the systems are called to achieve semiglobal output bipartite bounded consensus in probability. Finally, simulation results are raised to demonstrate the effectiveness of our proposed scheme.