5 papers · 1 filter
Automatic Basis Function Selection in Iterative Learning Control: A Sparsity-Promoting Approach Applied to an Industrial Printer
Tjeerd Ickenroth, Max van Haren, Johan Kon +3
Iterative learning control (ILC) techniques are capable of improving the tracking performance of control systems that repeatedly perform similar tasks by utilizing data from past i…
A Direct State-Space Realization of Discrete-Time Linear Parameter-Varying Input-Output Models
Johan Kon, Roland Tóth, Jeroen van de Wijdeven +2
A minimal state-space (SS) realization of an identified linear parameter-varying (LPV) input-output (IO) model usually introduces dynamic and nonlinear dependency of the state-spac…
Unconstrained Parameterization of Stable LPV Input-Output Models: with Application to System Identification
Johan Kon, Jeroen van de Wijdeven, Dennis Bruijnen +3
Ensuring stability of discrete-time (DT) linear parameter-varying (LPV) input-output (IO) models estimated via system identification methods is a challenging problem as known stabi…
Direct Learning for Parameter-Varying Feedforward Control: A Neural-Network Approach
Johan Kon, Jeroen van de Wijdeven, Dennis Bruijnen +3
The performance of a feedforward controller is primarily determined by the extent to which it can capture the relevant dynamics of a system. The aim of this paper is to develop an…
Cross-Coupled Iterative Learning Control for Complex Systems: A Monotonically Convergent and Computationally Efficient Approach
Leontine Aarnoudse, Johan Kon, Koen Classens +5
Cross-coupled iterative learning control (ILC) can achieve high performance for manufacturing applications in which tracking a contour is essential for the quality of a product. Th…