Adaptive iterative learning control for a class of non-linearly parameterised systems with input saturations

DOI10.1080/00207721.2014.911422zbMath1333.93148OpenAlexW2092475168MaRDI QIDQ2798433

Zhongsheng Hou, Honghai Ji, Ruikun Zhang, Chenkun Yin

Publication date: 12 April 2016

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

Full work available at URL: https://doi.org/10.1080/00207721.2014.911422

zbMATH Keywords

adaptive iterative learning control (AILC)input saturationscomposite energy function (CEF)nonlinearly parameterized systems

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Nonlinear systems in control theory (93C10) Adaptive control/observation systems (93C40) Control/observation systems governed by ordinary differential equations (93C15)

Related Items (3)

Bounded‐input iterative learning control: Robust stabilization via a minimax approach ⋮ Model-Free control performance improvement using virtual reference feedback tuning and reinforcement Q-learning ⋮ Input–output‐driven gain‐adaptive iterative learning control for linear discrete‐time‐invariant systems

Cites Work

• On reference governor in iterative learning control for dynamic systems with input saturation
• Iterative learning control design based on composite energy function with input saturation
• Robust iterative learning control for a class of nonlinear systems.
• Model-based iterative learning control with a quadratic criterion for time-varying linear systems
• Adaptive ILC for a class of discrete-time systems with iteration-varying trajectory and random initial condition
• Robust ℋ︁_∞ PID control for multivariable networked control systems with disturbance/noise attenuation
• On D-type and P-type ILC designs and anticipatory approach
• Initial shift issues on discrete-time iterative learning control with system relative degree
• Adaptive control of nonlinearly parameterized systems: a nonsmooth feedback framework
• Adaptive Repetitive Control for a Class of Nonlinearly Parametrized Systems
• A Unified Adaptive Iterative Learning Control Framework for Uncertain Nonlinear Systems

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