Sharif Digital Repository

EDMC is an extended version of the dynamic matrix control (DMC) approach to control nonlinear processes. In this method, control input is determined based on linear model approximation of the process in each control/optimization interval. The difference between linear and nonlinear models of the process is considered as the known part of the feedback signal in DMC control formulation. Usually the fixed point or the secant method is applied to reduce the difference between two models. In this paper, an EDMC controller is designed for a DC-DC power converter of the boost type. The behavior of the scheme is discussed with the transient and steady state response to step and sinusoidal... 

An application of a new controller order reduction technique with stability and performance preservation based on linear matrix inequality optimization to an active suspension system is presented. In this technique, the rank of the residue matrix of a proper rational approximation of a high-order H∞controller subject to the H∞-norm of a frequency-weighted error between the approximated controller and the high-order H∞ controller is minimized. However, because solving this matrix rank minimization problem is very difficult, the rank objective function is replaced with a nuclear-norm that can be reduced to a semidefinite program so that it can be solved efficiently. Application to the active... 

H∞ controller order reduction with stability and performance preservation pose unique challenges to designers. In the paper, an approach for controller order reduction based on minimization of the rank of a matrix variable, subject to linear matrix inequality constraints, is presented. In this approach, the rank of a residue matrix of a high-order controller subject to the error between the loop gain of the closed-loop nominal system and the loop gain of the closed-loop system with the reduced order controller is minimized. However, since solving this matrix rank minimization problem is very difficult, the rank objective function is replaced with the nuclear-norm that can be reduced to a... 

We present an application of a new controller order reduction technique with stability and performance preservation based on linear matrix inequality optimization to an active suspension system. In this technique, the rank of the residue matrix of a proper rational approximation of a high-order H ∞ controller subject to the H∞ norm of a frequency-weighted error between the approximated controller and high-order H∞ controller is minimized. However, since solving this matrix rank minimization problem is very difficult, the rank objective function is replaced with the nuclear-norm that can be reduced to a semidefinite program, so that it can be solved efficiently. Application to the active... 

This paper considers the problem of stabilizing a class of linear time-invariant large-scale systems composed of a number of subsystems using several local dynamic output feedback controllers. For this problem, a sufficient condition on each closed-loop individual subsystem is derived under which the decentralized controller composed of the local controllers designed for individual subsystems, achieves stability for the overall system. This condition is used to convert the decentralized stabilization problem to a set of the H∞ disturbance rejection subproblems  

An application of a continuous-time H∞ control to a flexible transmission system is presented. This approach has been proposed in order to assure high control performance in the presence of large load variation on the system. In this approach, the loading variations are considered as the multiplicative perturbation of the nominal plant. The desired specifications are enforced in the H∞ problem as the constraints on weighting functions. After an initial design procedure, the parameters of weighting functions, in order to obtain the desired performances, are tuned and then the final weighting functions are derived. The simulation results for three different loadings are given and compared  

This paper considers the problem of stabilizing a class of linear time-invariant large-scale systems composed of a number of subsystems using several local dynamic output feedback controllers. For this problem, a sufficient condition on each closed-loop individual subsystem is derived under which the decentralized controller composed of the local controllers designed for individual subsystems, achieves stability for the overall system. This condition is used to convert the decentralized stabilization problem to a set of the H∞ disturbance rejection subproblems  

A two dimensional rectangular microchannel with circular micropillars was modeled in the presence of an electric field. Continuity and Navier-Stokes equations were solved along with convection-diffusion equation using finite element method. Reaction phenomenon was applied via a partial differential equation on the reaction surfaces and electric force was added as a source term to the transport equations. Velocity, concentration and electric potential distributions were obtained, with the aid of which, capture efficiency and average surface concentration of reaction surfaces were calculated. To ameliorate the reaction rate, different designs of reaction surfaces were investigated; the designs... 

Background: Ataxia-telangiectasia (A-T) is a rare autosomal recessive disorder caused by mutations in the ataxia telangiectasia mutated (ATM) gene. A-T patients manifest considerable variability in clinical and immunological features, suggesting the presence of genetic modifying factors. A striking heterogeneity has been observed in class switching recombination (CSR) in A-T patients which cannot be explained by the severity of ATM mutations. Methods: To investigate the cause of variable CSR in A-T patients, we applied whole-exome sequencing (WES) in 20 A-T patients consisting of 10 cases with CSR defect (CSR-D) and 10 controls with normal CSR (CSR-N). Comparative analyses on modifier... 

Background: Ataxia-telangiectasia (A-T) is a rare autosomal recessive disorder caused by mutations in the ataxia telangiectasia mutated (ATM) gene. A-T patients manifest considerable variability in clinical and immunological features, suggesting the presence of genetic modifying factors. A striking heterogeneity has been observed in class switching recombination (CSR) in A-T patients which cannot be explained by the severity of ATM mutations. Methods: To investigate the cause of variable CSR in A-T patients, we applied whole-exome sequencing (WES) in 20 A-T patients consisting of 10 cases with CSR defect (CSR-D) and 10 controls with normal CSR (CSR-N). Comparative analyses on modifier... 

Cell separation is a key step in many biomedical research areas including biotechnology, cancer research, regenerative medicine, and drug discovery. While conventional cell sorting approaches have led to high-efficiency sorting by exploiting the cell's specific properties, microfluidics has shown great promise in cell separation by exploiting different physical principles and using different properties of the cells. In particular, label-free cell separation techniques are highly recommended to minimize cell damage and avoid costly and labor-intensive steps of labeling molecular signatures of cells. In general, microfluidic-based cell sorting approaches can separate cells using “intrinsic”... 

Recent advances in biomaterials, microfabrication, microfluidics, and cell biology have led to the development of organ-on-a-chip devices that can reproduce key functions of various organs. Such platforms promise to provide novel insights into various physiological events, including mechanisms of disease, and evaluate the effects of external interventions, such as drug administration. The neuroscience field is expected to benefit greatly from these innovative tools. Conventional ex vivo studies of the nervous system have been limited by the inability of cell culture to adequately mimic in vivo physiology. While animal models can be used, their relevance to human physiology is uncertain and... 

We investigate large wireless networks subject to security constraints. In contrast to point-to-point, interferencelimited communications considered in prior works, we propose active cooperative relaying-based schemes. We consider a network with nl legitimate nodes, ne eavesdroppers, and path loss exponent α ≥ 2. As long as n2e (log(ne))γ = o(nl ), for some positive γ , we show that one can obtain unbounded secure aggregate rate. This means zero-cost secure communication, given fixed total power constraint for the entire network. We achieve this result through: 1) the source using Wyner randomized encoder and a serial (multi-stage) block Markov scheme, to cooperate with the relays and 2) the... 

Investigating the impact of geological uncertainty (i.e., spatial distribution of fractures) on reservoir performance may aid management decisions. The conventional approach to address this is to build a number of possible reservoir models, upscale them, and then run flow simulations. The problem with this approach is that it is computationally very expensive. In this study, we use another approach based on the permeability contrasts that control the flow, called percolation approach. This assumes that the permeability disorder of a rock can be simplified to either permeable or impermeable. The advantage is that by using some universal laws from percolation theory, the effect of the complex... 

Droplet-based microfluidic systems have been employed to manipulate discrete fluid volumes with immiscible phases. Creating the fluid droplets at microscale has led to a paradigm shift in mixing, sorting, encapsulation, sensing, and designing high throughput devices for biomedical applications. Droplet microfluidics has opened many opportunities in microparticle synthesis, molecular detection, diagnostics, drug delivery, and cell biology. In the present review, we first introduce standard methods for droplet generation (i.e. passive and active methods) and discuss the latest examples of emulsification and particle synthesis approaches enabled by microfluidic platforms. Then, the applications... 

Recently, a new class of binary codes for overloaded CDMA systems are proposed that not only has the ability of errorless communication but also suitable for detecting active users. These codes are called COWDA. In [1], a Maximum Likelihood (ML) decoder is proposed for this class of codes. Although the proposed scheme for coding/decoding shows impressive performance, the decoder can be significantly improved. In this paper, by assuming practical conditions for the traffic in the system, we suggest and prove an algorithm that increases the performance of the decoder several orders of magnitude (the Bit-Error-Rate (BER) is divided by a factor of about 400 in some E b/N0's). The algorithm... 

In this paper we present new methods to estimate the effective permeability (keff) of heterogeneous porous media with a wide distribution of permeabilities and various underlying structures, using percolation concepts. We first set a threshold permeability (kth) on the permeability density function and use standard algorithms from percolation theory to check whether the high permeable grid blocks (i.e., those with permeability higher than kth) with occupied fraction of “p” first forms a cluster connecting two opposite sides of the system in the direction of the flow (high permeability flow pathway). Then we estimate the effective permeability of the heterogeneous porous media in different... 

It has long been understood that flow behavior in heterogeneous porous media is largely controlled by the continuity of permeability contrasts. With this in mind, we are looking in new methods for a fast estimation of the effective permeability which concentrates on the properties of the percolating cluster. From percolation concepts we use a threshold permeability value (Kth) by which the gridblocks with the highest permeability values connect two opposite side of the system in the direction of the flow. Those methods can be applied to heterogeneous media of a range of permeabilities distribution and various underlying structures. We use power law relations and weighted power averages that... 

Precise prediction of Remaining Useful Life (RUL) within the transportation industry is essential for cost reduction and enhanced energy efficiency, focusing on extending the operational lifespan of proton exchange membrane fuel cells (PEMFCs). In pursuit of this objective, this study employs data-driven prediction methodologies centered on deep neural networks and transfer learning. The fundamental premise is that these approaches hinge on the compatibility of functional conditions across diverse datasets. Multiple strategies, amalgamating transfer learning, and deep neural networks, are introduced to forecast the PEMFC stack's behavior and its associated RUL. Network hyperparameters are...