Residual neural network-based observer design for continuous stirred tank reactor systems

DOI10.1016/j.cnsns.2023.107592zbMath1530.93141OpenAlexW4387363974MaRDI QIDQ6144078

Song Chen, Zhi-Gang Ren, Tehuan Chen, Shi Liu

Publication date: 5 January 2024

Published in: Communications in Nonlinear Science and Numerical Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cnsns.2023.107592

zbMATH Keywords

observer designCSTRresidual neural networknonlinear isolationsectoral constraints

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Observers (93B53)

Cites Work

• System identification and control design of a nonlinear continuously stirred tank reactor
• Event-triggered asynchronous sliding mode control of CSTR based on Markov model
• Adaptive fuzzy backstepping control for a two continuous stirred tank reactors process based on dynamic surface control approach
• Artificial neural networks in structural dynamics: a new modular radial basis function approach vs. convolutional and feedforward topologies
• Analysis on existence of compact set in neural network control for nonlinear systems
• Observability and Observers for Nonlinear Systems
• Safety Verification and Robustness Analysis of Neural Networks via Quadratic Constraints and Semidefinite Programming
• Stability Analysis Using Quadratic Constraints for Systems With Neural Network Controllers
• State estimation for linear hybrid systems with periodic jumps and unknown inputs
• Real‐time neural observer‐based controller for unknown nonlinear discrete delayed systems
• Noise-to-state practical stability and stabilization of random neural networks

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