A5031410287- Control Systems and Identification
- Advanced Control Systems Optimization
- Fault Detection and Control Systems
- Particle accelerators and beam dynamics
- Superconducting Materials and Applications
- Stability and Control of Uncertain Systems
- Iterative Learning Control Systems
- Structural Health Monitoring Techniques
- Model Reduction and Neural Networks
- Advanced Control Systems Design
- Nuclear reactor physics and engineering
- Magnetic confinement fusion research
- Electromagnetic Launch and Propulsion Technology
- Particle Accelerators and Free-Electron Lasers
- Piezoelectric Actuators and Control
- Analog and Mixed-Signal Circuit Design
European Organization for Nuclear Research
2017-2020
École Polytechnique Fédérale de Lausanne
2014-2018
Cleveland State University
2011
Summary A new robust controller design method that satisfies the H ∞ criterion is developed for linear time‐invariant single‐input single‐output (SISO) systems. data‐driven approach implemented in order to avoid unmodeled dynamics associated with parametric models. This uses fixed‐order controllers satisfy frequency domain. The necessary and sufficient conditions existence of such are presented by a set convex constraints. These also extended systems frequency‐domain uncertainties polytopic...
A new data-driven approach using the frequency response function (FRF) of a system is proposed for designing robust-fixed structure digital controllers particle accelerators' power converters. This design method ensures that dynamics are captured and avoid problem unmodeled associated with parametric models. The H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> robust performance condition can be represented by set convex constraints...
A new data‐driven iterative learning control methodology is presented which uses the frequency response data of a system in order to avoid problem unmodelled dynamics associated with low‐order parametric models. convex optimisation formulated design filters such that convergence criterion minimised. Since used obtaining these filters, robustness ensured by eliminating uncertainty modelling process. The effectiveness method illustrated considering case study where proposed scheme applied...
Accurate control of power converters is a vital activity in large physics projects. Several different scenarios may coexist, including regulation circuit’s voltage, current, or field strength within magnet. Depending on the type facility, reference value be changed asynchronously synchronously with other circuits. Synchronous changes demand under cyclic timing system. In cases, calculated real-time by an outer loop some quantity, such as tune beam synchrotron. The stage unipolar bipolar...
Summary In this paper, a new data‐driven method for designing robust controllers is proposed systems with sector‐bounded nonlinearities and multimodel uncertainties. The results from the circle criterion are used to generate necessary sufficient convex constraints that guarantee stability of closed‐loop system. main feature approach only frequency response data linear part system guaranteeing nonlinear Additionally, optimization problem formulated ensure performance respect fundamental...
A new model-reference data-driven approach is presented for synthesizing controllers the CERN power converter control system. This method uses frequency response function (FRF) of a system in order to avoid problem unmodeled dynamics associated with low-order parametric models. For this particular application, it shown that convex optimization can be formulated H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> sense shape closed-loop FRF...
In this paper, a new method for designing robust fixed-order H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> discrete-time controllers is presented. The controller structure two-degree of freedom polynomial the RST-type. A data-driven approach implemented design process in order to capture unmodeled dynamics that may exist with parametric models. performance condition can be represented by set convex constraints respect parameters RST...
A new method for robust fixed-order H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> controller design uncertain time-delayed MIMO systems is presented. It shown that the performance condition can be represented by a set of convex constraints with respect to parameters linearly parameterized primary in Smith predictor structure. Therefore, obtained optimization. The proposed will applied stable models dead-time and multimodel...
Abstract The data-driven control approach is a methodology in which controller designed without the need of model. Parametric uncertainties and associated unmodeled dynamics are therefore irrelevant; only source uncertainty comes from measurement process. CERN Power Converter Control Libraries (CCLIBS) have been updated to include H-infinity methods recently proposed literature. In particular, two-step convex optimization algorithm performed for obtaining 2-degree-of-freedom parameters....