Sharif Digital Repository

In the present work, a fuzzy supervisory control approach combined with an adaptive model predictive controller (AMPC), has been proposed to maximize the productivity of an anaerobic digestion (AD) process, while keeping the operation stable. In the proposed hierarchal control strategy, the set-point of the inner loop is provided by a supervisory controller. In the inner loop an AMPC has been applied to achieve the desired methane production rate by manipulating the feed flow rate. The AMPC is designed based on the auto-regressive moving average (ARMA) model whose parameters are updated at each sampling time to make the controller more robust against uncertainties and external loads. In the... 

A dc-dc resonant converter has the advantage of overcoming switching losses and electromagnetic interference which are the main limitations of high frequency power converters. Nevertheless, the modeling and stability analysis of dc-dc resonant converters are considerably more complex than pulsewidth modulation counterparts. The conventional averaged linearized model of the resonant converter has limitations due to averaging and linearization. First of all, the linearized model has large modeling error in presence of large variations of reference voltage and input voltage. Furthermore, Converging area for stabilizing controllers is smaller in the averaged model. In order to overcome these... 

The demand for bidirectional DC/DC converters is increasing because of their potential capability for sustainable energy conversion systems where the power is to be captured from or stored in energy storage elements. This paper presents a three-phase series resonant bidirectional converter which is suitable for high power applications. The converter consists of two three-phase full bridge networks, the resonant tanks and a high frequency three-phase transformer. All switches can work either in ZVS or ZCS mode. The voltage drop on leakage inductances is minimized by choosing the switching frequency close to the resonant frequency, allowing high efficient power conversion. The phasor analysis... 

Single-phase power factor correction (PFC) converter circuits are non-linear systems due to the contribution of their multiplier. This non-linearity causes difficulties in analysis and design. Models that reduce the system to a linear system involve considerable approximation, and produce results that are susceptible to instability problems. In this paper a piecewise affine (PWA) system is introduced for describing the nonlinear averaged model. Then robust output feedback controllers are established in terms of the linear matrix inequality (LMI). Simulation and experiments results show the effectiveness of the proposed control method  

Bitcoin as the current leader in cryptocurrencies is a new asset class receiving significant attention in the financial and investment community and presents an interesting time series prediction problem. In this paper, some forecasting models based on classical like ARIMA and machine learning approaches including Kriging, Artificial Neural Network (ANN), Bayesian method, Support Vector Machine (SVM) and Random Forest (RF) are proposed and analyzed for modelling and forecasting the Bitcoin price. While some of the proposed models are univariate, the other models are multivariate and as a result, the maximum, minimum and the opening daily price of Bitcoin are also used in these models. The... 

This paper proposes a decentralized algorithm to organize an ad-hoc sensor network into clusters. Each sensor operates independently, monitoring communication among others. Those sensors which have many neighbors that are not already part of a cluster are likely candidates to creating a new cluster by declaring themselves to be a new cluster-head. The Clustering Algorithm via Deadline Timer (CADT) provides a protocol whereby this can be achieved and the process continues until all sensors are part of a cluster. Because of the difficulty of analyses simplified models are used to study and abstract its performance. A simple formula to estimate the number of clusters which will be formed in an... 

Road roughness-induced vibrations are the main source of fatigue damage accumulation in vehicles. Hence, road surface profile modeling and simulation are of high importance when it comes to vehicle fatigue damage assessment. This research focuses on uncovering the statistical distributions that describe the characteristics of road loads that affect fatigue damage accumulation. Particle filtering is deployed to estimate the log-volatility of the road surface profile by assuming a random walk behavior for the hidden log-volatility. The skew-normal distribution with three parameters is fitted to the estimated log-volatility. The inferred parameters are used for synthesizing artificial road...