Tracking control based on recurrent neural networks for nonlinear systems with multiple inputs and unknown deadzone

DOI10.1155/2012/471281zbMath1256.93054OpenAlexW1999056513WikidataQ58695265 ScholiaQ58695265MaRDI QIDQ1938206

J. Humberto Pérez-Cruz, Eduardo Ruiz-Velazquez, Gualberto Solis-Perales, José de Jesús Rubio

Publication date: 4 February 2013

Published in: Abstract and Applied Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2012/471281

Mathematics Subject Classification ID

Nonlinear systems in control theory (93C10) Adaptive control/observation systems (93C40) Control/observation systems governed by ordinary differential equations (93C15)

Related Items (1)

Proportional derivative control with inverse dead-zone for pendulum systems

Cites Work

• Nonlinear mathematical modeling in pneumatic servo position applications
• Composite tracking control for generalized practical synchronization of Duffing-Holmes systems with parameter mismatching, unknown external excitation, plant uncertainties, and uncertain deadzone nonlinearities
• System identification using multilayer differential neural networks: a new result
• Robust adaptive control of a class of nonlinear systems with unknown dead-zone.
• Robust adaptive neurocontrol of SISO nonlinear systems preceded by unknown deadzone
• Influence of control valve delay and dead zone on the stability of a simple hydraulic positioning system
• Neural networks for modelling and control of dynamic systems. A practitioner's handbook
• Adaptive control of plants with unknown dead-zones
• Deadzone compensation in motion control systems using neural networks
• Neuro-Fuzzy Control of Industrial Systems with Actuator Nonlinearities
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