Sharif Digital Repository

Price of oil is important for the economies of oil exporting and oil importing countries alike. Therefore, insight into the likely future behaviour and patterns of oil prices can improve economic planning and reduce the impacts of oil market fluctuations. This paper aims to improve the application of Artificial Neural Network (ANN) techniques to prediction of oil price. We develop a dynamic Nonlinear Auto Regressive model with eXogenous input (NARX) as a form of ANN to account for the time factor. We estimate the model using macroeconomic data from OECD countries. In order to compare the results, we develop time series and ANN static models. We then use the output of time series model to... 

Nowadays, exoskeletons have been gaining popularity due to their potential use in rehabilitation and augmentation. These robots often utilize series elastic actuators to facilitate compliant interaction with the human. Numerous studies have been carried out with the purpose of identification and control of these type of actuators. The goal of this paper is to provide a method for dynamic modeling and identification of series elastic actuators. This model is then used in the control loop as a feed-forward term to eliminate the actuator's dynamics. Each series elastic actuator used in the Sharif wearable robot, uses a brushless DC motor, a torsional spring, a harmonic drive, a timing belt, a... 

This research aims to optimize a multi-zone Air Handling Unit's (AHU) energy consumption by using a Non-linear Model Predictive Control (NMPC) approach. In this paper, Genetic Algorithm (GA) and Non-linear autoregressive network with exogenous inputs (NARX) have been utilized to design NMPC for a multi-zone AHU. The NMPC problem could be divided into two main sections: internal model and the optimizer. NARX serves as the controller's internal model to predict the building's thermal dynamics. GA is then used to solve the NMPC problem and find the optimal value of the control signals at each time step. The proposed NMPC jointly minimizes energy consumption of the AHU and the deviation from the...