A One-step Approach for Centralized Overactuated Motion Control of a Prototype Reticle Stage

Next-generation motion stages are envisaged to be lightweight to meet stringent demands regarding accuracy and throughput. The lightweight stage design implies flexible dynamical behavior, which is foreseen to be severely excited due to increasing acceleration forces. The aim of this paper is to exploit additional actuators and sensors to explicitly control the flexible dynamic behavior. A systematic weighting filter design procedure is introduced which is tailored to next-generation motion stages. The presented procedure naturally connects to existing robust control techniques. The procedure is applied to an experimental next-generation reticle stage confirming performance enhancement by exploiting additional actuators and sensors beyond traditional performance limitations.Team Jan-Willem van Wingerde

Comparing multivariable uncertain model structures for data-driven robust control: Visualization and application to a continuously variable transmission

The selection of uncertainty structures is an important aspect of system identification for robust control. The aim of this paper is to provide insight into uncertain multivariable systems for robust control. A unified method for visualizing model sets is developed by generating Bode plots of multivariable uncertain systems, both in magnitude and phase. In addition, these model sets are compared from the viewpoint of the control objective, allowing a quantitative analysis as well. An experimental case study on an automotive transmission application demonstrates these connections and confirms the importance of the developed framework for control applications. In addition, the experimental results provide new insights into the shape of associated model sets by using the presented visualization procedure. Both the theoretical and experimental results confirm that a recently developed robust-control-relevant uncertainty structure outperforms general dual-Youla-Kučera uncertainty, which in turn outperforms traditional uncertainty structures, including additive uncertainty.Team Jan-Willem van Wingerde

Conjugate Gradient MIMO Iterative Learning Control Using Data-Driven Stochastic Gradients

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 data-driven method for iterative learning control that is suitable for massive MIMO systems through the use of efficient unbiased gradient estimates. A stochastic conjugate gradient descent algorithm is developed that uses dedicated experiments to determine the conjugate search direction and optimal step size at each iteration. The approach is illustrated on a multivariable example, and it is shown that the method is superior to both the earlier stochastic gradient descent and deterministic conjugate gradient descent methods. Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Team Jan-Willem van Wingerde

Bode Analysis of Uncertain Multivariable Systems

Bode plots are crucial for frequency domain analysis of SISO systems. The aim of this paper is to develop a complete approach for Bode plots of multivariable uncertain systems for both the magnitude and phase. The magnitude is based on the singular values. The phase is based on the phase spread of the numerical range. An IQC-based approach is pursued to provide both the magnitude and phase. A simulation example shows that the presented approach allows the generation of multivariable Bode plots of multivariable uncertain systems.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Team Jan-Willem van Wingerde

Neural Network Training Using Closed-Loop Data: Hazards and an Instrumental Variable (IVNN) Solution

An increasing trend in the use of neural networks in control systems is being observed. The aim of this paper is to reveal that the straightforward application of learning neural network feedforward controllers with closed-loop data may introduce parameter inconsistency that degrades control performance, and to provide a solution. The proposed method employs instrumental variables to ensure consistent parameter estimates. A nonlinear system example reveals that the developed instrumental variable neural network (IVNN) approach asymptotically recovers the optimal solution, while pre-existing approaches are shown to lead to inconsistent estimates.Team Jan-Willem van Wingerde

Gaussian Process Repetitive Control With Application to an Industrial Substrate Carrier System With Spatial Disturbances

Repetitive control (RC) can perfectly attenuate disturbances that are periodic in the time domain. The aim of this article is to develop an RC approach that compensates for disturbances that are time-domain nonperiodic but are repeating in the position domain. The developed position-domain buffer consists of a Gaussian process (GP), which is learned using appropriate dynamic filters and nonequidistant data. This approach estimates position-domain disturbances resulting in perfect compensation. The method is successfully applied to a substrate carrier system, demonstrating performance robustness against time-domain nonperiodic disturbances that are amplified by traditional RC. Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Team Jan-Willem van Wingerde

Frequency Response Data-driven LPV Controller Synthesis for MIMO Systems

The linear parameter-varying framework enables systematic control design approaches to meet increasing performance requirements and complexity of systems. The aim of this paper is to develop local frequency response data-based analysis and synthesis conditions for multiple-input multiple-output linear parameter-varying systems to facilitate fast tuning. Key advantages are local stability and performance guarantees and a global controller parameterization. The effectiveness of the proposed methods are evaluated based on a simulation example.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Team Jan-Willem van Wingerde

A Fast Smoothing-Based Algorithm to Generate l_∞-Norm Constrained Signals for Multivariable Experiment Design

Handling peak amplitude constraints, or equivalently l∞-norm constraints, is an important application demand in experiment design for system identification. The aim of this letter is to present a method for the design of excitation signals with prescribed power spectrum under l∞-norm constraints for systems with many inputs and outputs. The method exploits an exponential smoothing function in an iterative algorithm. Fast convergence is achieved by a computationally efficient construction of the gradient and the Hessian matrix. Experimental results show excellent convergence behavior that overcomes local minima, while significantly reducing computation time compared to existing techniques. Accepted Author ManuscriptTeam Jan-Willem van Wingerde

Uncertain uncertainty in data-driven stochastic optimization: towards structured ambiguity sets

Ambiguity sets of probability distributions are a prominent tool to hedge against distributional uncertainty in stochastic optimization. The aim of this paper is to build tight Wasserstein ambiguity sets for data-driven optimization problems. The method exploits independence between the distribution components to introduce structure in the ambiguity sets and speed up their shrinkage with the number of collected samples. Tractable reformulations of the stochastic optimization problems are derived for costs that are expressed as sums or products of functions that depend only on the individual distribution components. The statistical benefits of the approach are theoretically analyzed for compactly supported distributions and demonstrated in a numerical example.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Team Dimitris BoskosTeam Jan-Willem van Wingerde

Frequency Response Data-Based LPV Controller Synthesis Applied to a Control Moment Gyroscope

Control of systems with operating condition-dependent dynamics, including control moment gyroscopes (CMGs), often requires operating condition-dependent controllers to achieve high control performance. The aim of this brief is to develop a frequency response data-driven linear parameter-varying (LPV) control design approach for single-input single-output (SISO) systems, which allows improved performance for a CMG. A stability theory using a closed-loop frequency response function (FRF) data is developed, which is subsequently used in a synthesis procedure that guarantees local stability and performance. Experimental results on a CMG demonstrate the performance improvements.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Team Jan-Willem van Wingerde