Adaptive Fault-Tolerant Tracking Control Algorithm for IoT Systems: Smart Building Case Study

Abstract

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.