A new neural network-based approach for self-tuning control of nonlinear SISO discrete-time systems

DOI10.1080/00207720903353583zbMath1206.93116OpenAlexW2095541982MaRDI QIDQ3072443

Jose I. Canelon, Gangbing Song, Leang San Shieh

Publication date: 3 February 2011

Published in: International Journal of Systems Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207720903353583

zbMATH Keywords

optimal controlneural networksnonlinear discrete-time systemsself-tuning control

Mathematics Subject Classification ID

Nonlinear systems in control theory (93C10) Discrete-time control/observation systems (93C55) Optimal stochastic control (93E20) Stochastic learning and adaptive control (93E35)

Cites Work

• Neural networks for control systems - a survey
• Multilayer feedforward networks are universal approximators
• A new approach for neural control of nonlinear discrete dynamic systems
• Self-tuning regulators—a state space approach
• Adaptive NN control for a class of discrete-time non-linear systems

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