Hybrid neural network controller for uncertain nonlinear discrete-time systems with non-symmetric dead zone and unknown disturbances

DOI10.1080/00207179.2022.2080117zbMath1520.93241OpenAlexW4293070035MaRDI QIDQ6134214

Uday Pratap Singh, Arun Bali, Kuldip Raj, Rahul Kumar

Publication date: 25 July 2023

Published in: International Journal of Control (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207179.2022.2080117

zbMATH Keywords

Lyapunov methodexternal disturbancesparticle swarm optimizationhybrid neural networkcontinuous stirred tank reactor (CSTR)non-linear uncertain systems

Mathematics Subject Classification ID

Approximation methods and heuristics in mathematical programming (90C59) Nonlinear systems in control theory (93C10) Control/observation systems with incomplete information (93C41) Discrete-time control/observation systems (93C55) Control/observation systems governed by functional relations other than differential equations (such as hybrid and switching systems) (93C30)

Related Items (1)

Adaptive control for cyber-physical systems under man-in-the-middle attacks with false data injections

Cites Work

• Adaptive neural network tracking design for a class of uncertain nonlinear discrete-time systems with dead-zone
• Stability analysis and synthesis of nonlinear time-delay systems via linear Takagi-Sugeno fuzzy models
• Discrete-time adaptive control of plants with unknown output dead-zones
• Novel fuzzy event-triggered adaptive control for nonlinear systems with input hysteresis
• Very fast linear and non-linear observers Part 2. Application to a power system
• Adaptive neural network control of nonlinear systems with unknown time delays
• Observer-based control of discrete-time Lipschitzian non-linear systems: application to one-link flexible joint robot

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