Sliding mode SISO control of model parameters for implicit dynamic feedback estimation of industrial tracking simulation systems
| Autor: | Reino Ruusu, Tommi Karhela, Valeriy Vyatkin, Gerardo Santillan Martinez |
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| Rok vydání: | 2017 |
| Předmět: |
ta113
model calibration 0209 industrial biotechnology Computer science Reliability (computer networking) Process (computing) sliding mode control Estimator 02 engineering and technology Kalman filter online simulation Sliding mode control Synchronization Noise 020901 industrial engineering & automation 020401 chemical engineering Control theory dynamic estimation dynamic process simulation Process control implicit dynamic feedback 0204 chemical engineering tracking simulation |
| Zdroj: | IECON Ruusu, R, Santillán Martínez, G, Karhela, T & Vyatkin, V 2017, Sliding mode SISO control of model parameters for implicit dynamic feedback estimation of industrial tracking simulation systems . in IECON 2017-43rd Annual Conference of the IEEE Industrial Electronics Society . IEEE Institute of Electrical and Electronic Engineers, pp. 6927-6932, 43rd Annual Conference of the IEEE Industrial Electronics Society, IECON 2017, Beijing, China, 29/10/17 . https://doi.org/10.1109/IECON.2017.8217211 |
| DOI: | 10.1109/iecon.2017.8217211 |
| Popis: | A tracking simulator is an online simulation system that achieves a permanent state synchronization with the targeted process by dynamically calibrating the model state after comparing process measurements with model results. Tracking simulators are a powerful industrial application that can be utilized as a plant-wide virtual sensor for process monitoring and diagnosis as well as a predictive tool to provide production forecasts based on the current state of the plant. In a tracking simulator, the online calibration is performed by a dynamic estimation method. One of the most adopted dynamic estimaton methods is implicit dynamic feedback, which is based on the adjustment of model parameter using feedback controllers to align simulation results and process outputs. Thus far, PI controllers have been the most popular approach for the implementation of implicit dynamic feedback estimators. Other feedback control techniques could be employed to improve the reliability of applications based on this estimation method. This paper presents an implicit dynamic feedback estimation approach based on sliding mode controllers (SMC) for industrial tracking simulation systems. In contrast to PI controllers, SMC controllers can be more easily tuned and they are robust against uncertainties related to the simulation model behavior and measurement noise. In this work, the SMC-based approach for estimation of tracking simulation systems is described, implemented and tested using a representative laboratory-scale process. |
| Databáze: | OpenAIRE |
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