68 citations · 234 across the 34 of their papers we have counts for
6 papers · 1 filter
Learning nonlinear feedforward: a Gaussian Process Approach Applied to a Printer with Friction
Max van Meer, Maurice Poot, Jim Portegies +1
Feedforward control is essential to achieving good tracking performance in positioning systems. The aim of this paper is to develop an identification strategy for inverse models of…
Intermittent Sampling in Repetitive Control: Exploiting Time-Varying Measurements
Johan Kon, Nard Strijbosch, Sjirk Koekebakker +1
The performance increase up to the sensor resolution in repetitive control (RC) invalidates the standard assumption in RC that data is available at equidistant time instances, e.g.…
Conjugate gradient MIMO iterative learning control using data-driven stochastic gradients
Leontine Aarnoudse, Tom Oomen
Data-driven iterative learning control can achieve high performance for systems performing repeating tasks without the need for modeling. The aim of this paper is to develop a fast…
Frequency Response Data Based LPV Controller Synthesis Applied to a Control Moment Gyroscope
Tom Bloemers, Roland Tóth, Tom Oomen
Control of systems with operating condition-dependent dynamics, including control moment gyroscopes, often requires operating condition-dependent controllers to achieve high contro…
Iterative learning control with discrete-time nonlinear nonminimum phase models via stable inversion
Isaac A Spiegel, Nard Strijbosch, Tom Oomen +1
Output reference tracking can be improved by iteratively learning from past data to inform the design of feedforward control inputs for subsequent tracking attempts. This process i…
Frequency-Domain Data-Driven Controller Synthesis for Unstable LPV Systems
Tom Bloemers, Roland Tóth, Tom Oomen
Synthesizing controllers directly from frequency-domain measurement data is a powerful tool in the linear time-invariant framework. Ever-increasing performance requirements necessi…