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Everything Is Under Control Everything is under control Citation for published version (APA): Heertjes, M. F. (2020). Everything is under control. Technische Universiteit Eindhoven. Document status and date: Published: 06/03/2020 Document Version: Publisher’s PDF, also known as Version of Record (includes final page, issue and volume numbers) Please check the document version of this publication: • A submitted manuscript is the version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website. • The final author version and the galley proof are versions of the publication after peer review. • The final published version features the final layout of the paper including the volume, issue and page numbers. Link to publication General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal. If the publication is distributed under the terms of Article 25fa of the Dutch Copyright Act, indicated by the “Taverne” license above, please follow below link for the End User Agreement: www.tue.nl/taverne Take down policy If you believe that this document breaches copyright please contact us at: [email protected] providing details and we will investigate your claim. Download date: 24. Sep. 2021 Everything is under control I Prof.dr.ir. Marcel Heertjes March 6, 2020 INAUGURAL LECTURE Everything is under control DEPARTMENT OF MECHANICAL ENGINEERING INAUGURAL LECTURE PROF.DR.IR. MARCEL HEERTJES Everything is under control Presented on March 6, 2020 at Eindhoven University of Technology Everything is under control 3 Introduction ‘Everything is under control’ refers to the sheer number of controls being used nowadays in high-precision systems. One example is stage systems in wafer scanners (the tool used to produce microchips), which have hundreds of control loops for their motion control [1]. This number is expected to increase as more and more (sub)systems are connected by control in a system-of-systems manner [2]. ‘Everything is under control’ also refers to the task that control engineering has in meeting system specifications and performances. Though control technology is often not visible from the outside as it is hidden within algorithms (hence the hidden technology [3]), high-precision systems can by no means meet specifications without this technology [4]. Lastly, ‘everything is under control’ imparts a feeling of ease, often against better judgement. Despite the impressive progress in mechatronics and hardware design, and regardless of the promotion of modern control technologies [27], the high-precision industry is still dominated by classical control concepts. In the inaugural lecture, the state-of-the-art in industrial motion control will first be highlighted using an example from a stage control system. This section aims to provide a view of where we stand in terms of motion control performance in industry and what room there is for the progression of motion control technologies. Secondly, two control scenarios will be discussed that aim for reflection on what future motion control may look like: (machine) learning in feedforward control and hybrid integrator-gain systems in feedback control. Both scenarios have been chosen in line with worldwide trends regarding data-based control [5] and nonlinear control for linear systems [6,7] and illustrate the context of industrial nonlinear control for high-precision systems, the area in which I am a part-time professor. Lastly, some thoughts are shared on the interplay between industry and the university, especially regarding research and education. 4 Prof.dr.ir. Marcel Heertjes Everything is under control 5 of the eight signals in gray. A distinction is made between the time interval of Motion control technology – scanning, i.e. where exposure takes place under constant velocity motion, and the time interval at which the system accelerates or decelerates in order to prepare a stage example (among other things) for exposure of the next field. As the data underlying the figure were obtained from a recently-produced stage system, one may expect state-of-the-art industrial motion control and the resulting tracking performance. In motion control, one basically distinguishes between two problems: the servo/ tracking problem and the regulator problem [8]. In the servo/tracking problem, we Observation 1: error signals inside the scanning interval are smaller in want the output of the controlled system to stay as close as possible to a reference magnitude than error signals outside of the scanning interval. trajectory. Think of the commanded meander pattern used in wafer scanners to This observation is in line with the fact that (servo) performance in wafer scanners enable exposure along the wafer [1]. In the regulator (or disturbance rejection) is mainly relevant when exposure takes place, i.e. in the scanning interval. A closer problem, the output of the controlled system subject to disturbances should be as look, however, reveals that the error at the beginning of the scanning interval is close as possible to a predetermined value. The servo/tracking problem is often significantly larger than the error closer to the end of the scanning interval, hence tackled by feedforward control, whereas the regulator problem is dealt with by the presence of a settling effect. feedback control. Observation 2: error signals both inside and outside of the scanning interval For many motion control systems, a significant source of servo error stems from the show reproducible behavior. servo problem, i.e. the setpoint profiles that we essentially provide ourselves. As a At the larger error levels, the spread among the different error signals becomes testament to this claim, consider Figure 1, which depicts an industrial wafer stage relatively small (the signals look alike), indicating the presence of reproducible system on its left. This shows the short-stroke stage during exposure of one of its behavior. There is a strong correlation between the setpoint (acceleration) profile many fields on the wafer. and the system’s response. As the setpoint is known beforehand and as we have a good understanding of the system through identification [9], we should be able to avoid this setpoint-induced part from occurring in the system’s response. 30 For wafer scanners, the importance of both observations stems from its relationship exposure field wafer with key performance indicators like machine overlay and throughput. Consider, short-stroke stage for example, the time needed to expose one field, which in Figure 1 equals 2.8 0 0.0476 seconds. Exposing 105 fields per wafer would thus lead to an upper -2.8 bound on throughput of about 720 wafers per hour, which exceeds the scanner’s specifications by a rough factor of three. Imagine the increase in throughput if one could simply expose while still accelerating (or decelerating). From a control point of view, however, one would experience a large hinderance due to the increase -30 0 0.0378 0.0854 0.1 of error magnitudes outside of the scanning interval, as previously discussed. But what if we could avoid the setpoint-induced error responses, leaving the Figure 1. (a) Wafer stage system. (b) Servo tracking performance of a stage system. magnitudes both inside and outside of the scanning interval equally small? On the righthand side, the figure shows the pointwise mean (in red) of eight measured servo error signals which resulted from applying eight identical setpoint For industrial high-precision mechatronics, the stage example considered does not profiles, as indicated by the scaled, dashed curve. The figure also shows the spread stand on its own. In fact, its system performance extrapolates well to many other application areas for the obvious reason of similarity in both system and control 6 Prof.dr.ir. Marcel Heertjes Everything is under control 7 design. Be it a CD player, wafer stage, component mounter or photocopier, all are Take a look at Figure 3, which shows a sample of 30 recently-produced stage represented by double integrator-based systems according to Newton’s second systems. In the sample, three different types are considered. Within each type, law and all use PID-based control designs [25]. ten different stage systems have been randomly selected. The figure shows the estimated benefit of the mean error responses in RMS values by (a) removing 3dB So, let’s continue with the stage example by considering the regulator problem as the reproducible part and (b) removing the frequency content below fbw . This well. Take Figure 2, which shows the frequency content of the previously-discussed shows room for improvement by factors of 2.4 × 3.1 = 7.4 (type 1), 2.9 × 1.9 = 5.5 error responses through cumulative power spectral density analysis. (type 2) and 4.2 × 3.8 = 16.0 (type 3), respectively. Also, the response outside of the scanning interval no longer significantly differs from the response inside the 30 2.8 scanning interval if one treats the reproducible part with appropriate care. 2.1 2.8 0 -2.8 100 10-1 -30 0 0 0.0378 0.0854 0.1 2.525250 2500 Figure 2. Frequency-domain evaluation. 10-2 Figure 3.
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