Dynamic neural observers and their application for identification and purification of water by ozone

DOI10.1134/S0005117906060051zbMath1120.93351OpenAlexW1968868435MaRDI QIDQ2457580

Alexander S. Poznyak, Isaac Chairez, Tatyana Poznyak

Publication date: 23 October 2007

Published in: Automation and Remote Control (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1134/s0005117906060051

Mathematics Subject Classification ID

Application models in control theory (93C95) Observability (93B07)

Related Items (8)

Passive learning and input-to-state stability of switched Hopfield neural networks with time-delay ⋮ Some new results on stability of Takagi-Sugeno fuzzy Hopfield neural networks ⋮ Robust stability of recurrent neural networks with ISS learning algorithm ⋮ Robust adaptive neurocontrol of SISO nonlinear systems preceded by unknown deadzone ⋮ Exponential \(\mathcal H_{\infty}\) stable learning method for Takagi-Sugeno fuzzy delayed neural networks: a convex optimization approach ⋮ Dr. Alexander Semionovich Poznyak Gorbatch: Biography ⋮ Sliding mode neurocontrol for the class of dynamic uncertain non-linear systems ⋮ An \(\mathcal H_{\infty}\) approach to stability analysis of switched Hopfield neural networks with time-delay

Cites Work

• Unnamed Item
• Linearization by output injection and nonlinear observers
• Simultaneous states and parameters estimation of an ozonation reactor based on dynamic neural network
• High-gain observers in the state and parameter estimation of robots having elastic joints
• Sliding controller design for non-linear systems
• A Luenberger-like observer for nonlinear systems
• Trajectory tracking in nonlinear systems via nonlinear reduced-order observers

This page was built for publication: Dynamic neural observers and their application for identification and purification of water by ozone