Robust high-order iterative learning control approach for two-dimensional linear discrete time-varying Fornasini–Marchesini systems with iteration-dependent reference trajectory
DOI10.1080/00207721.2021.1988188zbMath1486.93012OpenAlexW3206700519MaRDI QIDQ5073349
Publication date: 6 May 2022
Published in: International Journal of Systems Science (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/00207721.2021.1988188
extended high-order linear discrete inequalityhigh-order iterative learning control (HOILC)iteration-dependent reference trajectorytwo-dimensional linear discrete time-varying Fornasini-Marchesini systems (2-D LDTVFMS)
Sensitivity (robustness) (93B35) Discrete-time control/observation systems (93C55) Linear systems in control theory (93C05) Iterative learning control (93B47)
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Cites Work
- Two-dimensional state-space discrete models for hyperbolic partial differential equations
- On the disturbance properties of high order iterative learning control algorithms
- Iterative learning control design for linear discrete-time systems with multiple high-order internal models
- Two-dimensional linear systems
- Robust \(l_2\)-gain control for 2D nonlinear stochastic systems with time-varying delays and actuator saturation
- On robust Kalman filter for two-dimensional uncertain linear discrete time-varying systems: a least squares method
- Robust stabilization of constrained uncertain continuous-time fractional positive systems
- Robust iterative learning control with rectifying action for nonlinear discrete time-delayed systems
- Two-Dimensional Dissipative Control and Filtering for Roesser Model
- On iterative learning control with high-order internal models
- Analysis of iterative learning control with high-order internal models for fractional differential equations
- Unbiased Minimum Variance Fault and State Estimation for Linear Discrete Time-Varying Two-Dimensional Systems
- Iterative learning control design with high‐order internal model for discrete‐time nonlinear systems
- An E‐HOIM Based Data‐Driven Adaptive TILC of Nonlinear Discrete‐Time Systems for Non‐Repetitive Terminal Point Tracking
- A High-Order Internal Model Based Iterative Learning Control Scheme for Nonlinear Systems With Time-Iteration-Varying Parameters
- Realization Using the Fornasini-Marchesini Model for Implementations in Distributed Grid Sensor Networks
- Iterative learning control for 2-D linear discrete Fornasini–Marchesini model with input saturation
- A sufficient condition on the exponential stability of two-dimensional (2-D) shift-variant systems
- ℋ︁∞ and l2–l∞ filtering for two‐dimensional linear parameter‐varying systems
- Stochastic high‐order internal model‐based adaptive TILC with random uncertainties in initial states and desired reference points
- Adaptive iterative learning control for <scp>2D</scp> nonlinear systems with nonrepetitive uncertainties
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