Sharif Digital Repository

A robust multiple model adaptive control strategy using fuzzy fusion (RMMAC-FF) is presented in this paper. The main idea in multi-model controllers is to identify the best model of the system at any instant of time and apply the appropriate control input to it. RMMAC-FF, integrates a fuzzy robust controller, with the fuzzy multiple model adaptive estimation and a fuzzy switching to come up with a new strong methodology to control complex systems. Simulation results of the RMMAC-FF on a two-cart system, used as a benchmark problem, verify the theory and confirm the effectiveness of the proposed controller  

One of the distributed solutions for scaling Web Search Engines (WSEs) may be peer-to-peer (P2P) structures. P2P structures are successfully being used in many systems with lower cost than ordinary distributed solutions. However, the fact that they can also be beneficial for large-scale WSEs is still a controversial subject. In this paper, we introduce challenges in using P2P structures to design a large-scale WSE. Considering different types of P2P systems, we introduce possible P2P models for this purpose. Using some quantitative evaluation, we compare these models from different aspects to find out which one is the best in order to construct a large-scale WSE. Our studies indicate that... 

In this paper, a novel generalized predictive control (GPC) strategy using multiple models approach has been presented. The proposed strategy is realized based on the Takagi-Sugeno-Kang (TSK) fuzzy-based modeling for control of a tubular heat exchanger system. In this strategy, different operating environments of the system with varying parameters are first identified. Then for each environment, a linear model and its corresponding fuzzy predictive controller are designed. For demonstrating the effectiveness of the proposed approach, simulations are done and the results are compared with those obtained using the single model predictive control approach. The results can verify the validity of... 

Among the phenomenological hysteresis models, the Preisach model, Krasnosel'skii-Pokrovskii model, and Prandtl-Ishlinskii model have found extensive applications for modeling hysteresis in shape memory alloys and other smart actuators. Since the mathematical complexity of the identification and inversion problem depends directly on the type of phenomenological hysteresis modeling method, choosing a proper phenomenological model among the mentioned models for modeling the hysteretic behavior of shape memory alloy actuators is a task of crucial importance. Moreover, the accuracy of the hysteresis modeling method in characterizing shape memory alloy hysteretic behavior consequently affects the... 

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 use of ZrO2 nanoparticles is common in the Cu matrix to manufacture Cu/ZrO2 nanocomposites. Many approaches and parameters produce Cu/ZrO2 nanocomposites with an appropriate wear rate and other properties. Hence, proposing an accurate and reliable model was imperative. The main goal of this paper is to find out the best models among the ant colony optimization (ACO), gene expression programming (GEP), artificial bee colony (ABC), and gray wolf optimization algorithm (GWOA) to predict the wear rate of/ZrO2 nanocomposites. To the best of our knowledge, this is the first research that predicts Cu/ZrO2 nanocomposites wear rate using group modeling. To develop models, 105 data were collected...