Adaptive Fault-Tolerant Tracking Control Algorithm for IoT Systems: Smart Building Case Study
| Autor: | G. Kumar Venayagamoorthy, Inés Sittón, Javier Prieto, Sara Rodríguez, Fernando De la Prieta, Pastora Vega, Roberto Casado-Vara, José Luis Calvo-Rolle |
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| Rok vydání: | 2019 |
| Předmět: |
0209 industrial biotechnology
Temperature control Computer science Real-time computing Fault tolerance 02 engineering and technology Nonlinear control Tracking error 020901 industrial engineering & automation Control system 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Algorithm design Efficient energy use |
| Zdroj: | Advances in Intelligent Systems and Computing ISBN: 9783030200541 SOCO |
| DOI: | 10.1007/978-3-030-20055-8_46 |
| Popis: | In this paper, the problem of robust adaptive fault-tolerant tracking control with state-prediction performance is analyzed for a class of Iot temperature systems subject to accuracy states uncertainties and external disturbances. In order to ensure the efficiency of our new adaptive temperature control algorithm, we propose a new control strategy which is based on game theory consensus and prediction of accuracy future states to reduce the tracking error and improve the effectiveness of the algorithm. Compared with the existing results, a novel algorithm is developed to improve the operation of the monitoring and control of the Iot networks in order to increase the Energy efficiency of it. According with the simulation information provided by our investigation a new fault tolerant tracking error algorithm guaranteeing the robust tracking of the reference model. It shown that the predicted temperature signal is bounded by a small interval close to the collected temperature data. A case study result is provided to demonstrate the efficacy of the proposed adaptive fault-tolerant tracking control algorithm. |
| Databáze: | OpenAIRE |
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