Adaptive iterative learning control for nonlinear pure-feedback systems with initial state error based on fuzzy approximation

DOI10.1016/j.jfranklin.2013.11.018zbMath1395.93317OpenAlexW1987410779MaRDI QIDQ1659417

Junmin Li, Chunli Zhang

Publication date: 15 August 2018

Published in: Journal of the Franklin Institute (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jfranklin.2013.11.018

zbMATH Keywords

adaptive iterative learning controlfuzzy approximationnonlinear pure-feedback systemsinitial state error

Mathematics Subject Classification ID

Fuzzy control/observation systems (93C42) Nonlinear systems in control theory (93C10) Design techniques (robust design, computer-aided design, etc.) (93B51) Adaptive control/observation systems (93C40)

Related Items (7)

Iterative learning control for nonlinear stochastic systems with variable pass length ⋮ On the iterative learning control for stochastic impulsive differential equations with randomly varying trial lengths ⋮ On iterative learning control for MIMO nonlinear systems in the presence of time-iteration-varying parameters ⋮ Markov parameters identification and adaptive iterative learning control for linear discrete-time MIMO systems with higher-order relative degree ⋮ Analysis of iterative learning control for a class of fractional differential equations ⋮ Hierarchical recursive generalized extended least squares estimation algorithms for a class of nonlinear stochastic systems with colored noise ⋮ Adaptive fuzzy ILC of nonlinear discrete-time systems with unknown dead zones and control directions

Cites Work

• Unnamed Item
• Output-feedback adaptive fuzzy control for a class of nonlinear systems with input delay and unknown control directions
• Neuro-fuzzy control of underwater vehicle-manipulator systems
• Observer-based adaptive fuzzy tracking control for a class of uncertain nonlinear MIMO systems
• Fuzzy adaptive high-gain-based observer backstepping control for SISO nonlinear systems
• Fuzzy control of dithered chaotic systems via neural-network-based approach
• Fuzzy adaptive output feedback control for MIMO nonlinear systems
• Auto-structuring fuzzy neural system for intelligent control
• Iterative learning control for deterministic systems
• Robust iterative learning control for a class of nonlinear systems.
• On the design of observer-based fuzzy adaptive controller for nonlinear systems with unknown control gain sign
• Robust adaptive fuzzy control for a class of stochastic nonlinear systems with dynamical uncertainties
• Adaptive robust iterative learning control with dead zone scheme
• An adaptive PID learning control of robot manipulators
• Adaptive control for nonlinear MIMO time-delay systems based on fuzzy approximation
• Adaptive fuzzy learning control for a class of nonlinear dynamic systems
• A P-type iterative learning controller for robust output tracking of nonlinear time-varying systems
• A Unified Adaptive Iterative Learning Control Framework for Uncertain Nonlinear Systems
• Adaptive learning control of uncertain robotic systems

This page was built for publication: Adaptive iterative learning control for nonlinear pure-feedback systems with initial state error based on fuzzy approximation