How could data integrate with control? A review on data-based control strategy
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How could data integrate with control? A review on data-based control strategy Jing-Wen Huang1
· Jia-Wen Gao1
Received: 11 July 2020 / Revised: 15 August 2020 / Accepted: 12 September 2020 © Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract In recent years, data-driven research has attracted significant attention from both industry and academia due to its success in medical, transportation, finance and other fields. How could data tightly integrate with control is a hot issue being explored. This paper provides a brief survey on the relationship of data and control. Four types of data-based control studies are considered, namely post-identification control, direct data control, learning control, and observer-based control. The observer based control can provide real-time observation and estimation of the unknown dynamic systems. It has a great potential in solving complex online control problems. This paper classifies and analyzes the observer integrated control, covering the latest research progress and forecasting the development trend in this direction. This paper concludes with a summary advantages and disadvantages of data-based controls. Keywords Data-based control · Post-identification control · Direct data control · Learning control · Observer based control
1 Introduction For complex and large-scale plants, it is sometimes difficult to create an accurate control-oriented model based on the first principles, while model-based control is being extensively pursued. In the age of high technologies, extensive operational data of these complex systems can be obtained, which contain rich dynamic information of the system. The methods of big data and artificial intelligence have enabled us to investigate control designs that do not rely on models. The knowledge about the physical structure and general framework of the system is often enough for us to develop control designs. However, how to combine the extensive data with the control theory is also confronted with dichotomies such as offline and online, random and deterministic, iteration and convergence, speed and complexity, etc. Many scholars have conducted research in this area. Research results have been discussed in some review papers. These existing review papers are catered towards academic researchers
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Jing-Wen Huang [email protected] Jia-Wen Gao [email protected]
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who are interested in either offline modeling [1–3] or online data-driven control [4,5]. However, a comprehensive review starting from open-loop modeling with data to data-based closed-loop control is still needed. In this paper, we start from the combination of data and control to study the data-based controls that have appeared in the literature so far. We discuss how the data are combined with control. Some special data-based controls are discussed in detail. To be specific, the objectives of this paper include: (1) to present a systematic and comprehensive overview of data-based controls in terms of relationship between the control strategy and the measuremen
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