Sharif Digital Repository

The purpose of the paper presented here is to deal with the well-known linear generalized predictive control (LGPC) scheme based on multiple models strategy for a tubular heat exchanger system. In this control strategy, the operating environments of the system are first represented by multiple explicit linear models. Then the best model of the system is precisely identified by a novel intelligent decision mechanism (IDM), where is organized in association with the fuzzy adaptive Kalman filter and recursive weight generator approaches. As soon as the best model of the system is identified, the corresponding predictive control action is instantly implemented on the system. In order to... 

The track fusion combines individual tracks formed by different sensors. Tracks are usually obtained by Kalman Filter (KF), since it is suitable for real-time application. The KF is an optimal linear estimator when the measurement noise has a Gaussian distribution with known covariance. However, in practice, some of the sensors do not have these properties, and the traditional KF is not an optimal estimator. In this paper, a novel adaptive Kalman filter (NAKF) is proposed. In this approach, the measurement noise covariance is adjusted by using an introduced simple mathematical function of one variable, called the degree of matching (DoM), where it is defined on the basis of covariance...