A Novel Markov Chain Based ILC Analysis for Linear Stochastic Systems Under General Data Dropouts Environments
From MaRDI portal
Publication:4566933
DOI10.1109/TAC.2016.2638044zbMath1390.93887OpenAlexW2560699099MaRDI QIDQ4566933
Publication date: 27 June 2018
Published in: IEEE Transactions on Automatic Control (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1109/tac.2016.2638044
Related Items (18)
Iterative Learning Control on Nonlinear Stochastic Networked Systems with Non-Differentiable Dynamics ⋮ Iterative learning control for linear delay systems with deterministic and random impulses ⋮ Non-affine nonlinear stochastic systems with two ILC update laws under random data dropouts ⋮ Two novel iterative learning control schemes for systems with randomly varying trial lengths ⋮ Finite time asymmetric bipartite consensus for multi‐agent systems based on iterative learning control ⋮ Optimal input filtering for networked iterative learning control systems with packet dropouts and channel noises in both sides ⋮ Optimal input filters for iterative learning control systems with additive noises, random delays, and data dropouts in both channels ⋮ A two-dimensional approach to iterative learning control with randomly varying trial lengths ⋮ Iterative learning control for MIMO parabolic partial difference systems with time delay ⋮ A comparison of compensation methods for random input data dropouts in networked iterative learning control system ⋮ Robust stability of stochastic systems with varying delays: application to RLC circuit with intermittent closed-loop ⋮ A new approach to feedback feed-forward iterative learning control with random packet dropouts ⋮ Adaptive learning tracking for uncertain systems with partial structure information and varying trial lengths ⋮ Adaptive iterative learning control for MIMO nonlinear systems performing iteration-varying tasks ⋮ An optimal filter for updated input of iterative learning controllers with multiplicative and additive noises ⋮ Iterative learning control of multi-agent systems with random noises and measurement range limitations ⋮ A joint control protocol for a class of uncertain nonlinear systems with iteration-varying trial length ⋮ Convergence properties of two networked iterative learning control schemes for discrete-time systems with random packet dropout
This page was built for publication: A Novel Markov Chain Based ILC Analysis for Linear Stochastic Systems Under General Data Dropouts Environments
