55 citations · 236 across the 20 of their papers we have counts for
12 papers · 1 filter
Learning Based Model Predictive Control for Quadcopters with Dual Gaussian Process
Yuhan Liu, Roland Tóth
An important issue in quadcopter control is that an accurate dynamic model of the system is nonlinear, complex, and costly to obtain. This limits achievable control performance in…
Deep Identification of Nonlinear Systems in Koopman Form
Lucian Cristian Iacob, Gerben Izaak Beintema, Maarten Schoukens +1
The present paper treats the identification of nonlinear dynamical systems using Koopman-based deep state-space encoders. Through this method, the usual drawback of needing to choo…
Incremental Dissipativity based Control of Discrete-Time Nonlinear Systems via the LPV Framework
Patrick J. W. Koelewijn, Roland Tóth, Siep Weiland
Unlike for Linear Time-Invariant (LTI) systems, for nonlinear systems, there exists no general framework for systematic convex controller design which incorporates performance shap…
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…
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…
On the Use of the Smith-McMillan Form in Decoupling System Dynamics
Clarisse Pétua Bosman Barros, Hans Butler, Roland Tóth
In this paper, the use of the Smith-McMillan form in decoupling multiple-input multiple-output system dynamics is analyzed. In short, from a transfer matrix plant model one can obt…
Learning-based feedforward augmentation for steady state rejection of residual dynamics on a nanometer-accurate planar actuator system
Ioannis Proimadis, Yorick Broens, Roland Tóth +1
Growing demands in the semiconductor industry result in the need for enhanced performance of lithographic equipment. However, position tracking accuracy of high precision mechatron…
Nonlinear parameter-varying state-feedback design for a gyroscope using virtual control contraction metrics
Ruigang Wang, Patrick J. W. Koelwijn, Ian R. Manchester +1
In this paper, we present a virtual control contraction metric (VCCM) based nonlinear parameter-varying (NPV) approach to design a state-feedback controller for a control moment gy…
Nonlinear Tracking and Rejection using Linear Parameter-Varying Control
Patrick J. W. Koelewijn, Roland Tóth, Henk Nijmeijer +1
The Linear Parameter-Varying (LPV) framework has been introduced with the intention to provide stability and performance guarantees for analysis and controller synthesis for Nonlin…
Fundamental Lemma for Data-Driven Analysis of Linear Parameter-Varying Systems
Chris Verhoek, Roland Tóth, Sofie Haesaert +1
Based on the Fundamental Lemma by Willems et al., the entire behaviour of a Linear Time-Invariant (LTI) system can be characterised by a single data sequence of the system as long…
Data-Driven Predictive Control for Linear Parameter-Varying Systems
Chris Verhoek, Hossam S. Abbas, Roland Tóth +1
Based on the extension of the behavioral theory and the Fundamental Lemma for Linear Parameter-Varying (LPV) systems, this paper introduces a Data-driven Predictive Control (DPC) s…
Incremental Stability and Performance Analysis of Discrete-Time Nonlinear Systems using the LPV Framework
Patrick J. W. Koelewijn, Roland Tóth
The dissipativity framework is widely used to analyze stability and performance of nonlinear systems. By embedding nonlinear systems in an LPV representation, the convex tools of t…