Sharif Digital Repository

This paper proposes a novel decentralized control approach for islanded direct-current (DC) microgrids (MGs) based on model predictive control (MPC) to regulate the distributed generation unit (DGU) output voltages, i.e. the voltages of the point of common coupling (PCC). A local controller is designed for each DGU, in the presence of uncertainties, disturbances, and unmodeled dynamics. First, a discrete-time state-space model of an MG is derived. Afterward, an MPC algorithm is designed to perform the PCC voltage control. The proposed MPC scheme ensures that the PCC voltages remain within an acceptable range. Several simulation studies have been conducted to illustrate the effectiveness of... 

We have recently introduced a high-level extension for stochastic activity networks (SANs) called coloured stochastic activity networks (CSANs). CSANs have several distinguishing properties, which make them quite appropriate for modeling and evaluation of software performance and dependability. CSANs have introduced a construct called coloured place for data manipulation. A coloured place holds a list of tokens of a userdefined token type. CSAN models can be evaluated by state space analysis techniques or discrete-event simulation. However, their state spaces will become very large, even for a small CSAN model. For efficient evaluation of these models by state space analysis methods, we will... 

This paper proposes a novel representation of uncertain LTI fractional order systems based on the state-space model which contains both interval and polytopic uncertainties. First, a set of linear matrix inequalities, which are sufficient conditions, are presented for analyzing the robust stability of the mentioned systems. Then, some sufficient conditions are obtained for designing a feedback gain matrix to tackle the robust stabilization of the considered systems. Note that the concluded conditions of this paper are valid for fractional systems with a given constant derivative order α in 1 ≤ α < 2 and also, can be employed conservatively for α in 0 < α < 1. Finally, through two numerical... 

In this paper, by introducing a new general state-space form for uncertain linear time-invariant fractional-order systems subjected to interval and polytopic uncertainties, two problems including robust stability analysis and robust stabilization of the presented systems are investigated. Subsequently, two sufficient conditions in terms of several linear matrix inequalities for the problems mentioned are concluded as two separate theorems. It is assumed that the fractional order α is a known constant belonging to 0 < α < 1. Simulation results of two different numerical examples demonstrate that the provided sufficient conditions are applicable and effective for tackling robust stability and... 

This brief presents a systematic approach for the design of sparse dynamic output feedback control structures. A supplementary complexity cost function term is used to promote sparsity in the structure while optimizing an H2 performance cost simultaneously. Optimization problems in which a combinatorial sparsity measure is combined with a nonlinear performance cost function are NP-hard. NP-hard problems do not have tractable solutions, requiring either a numerical solution or a relaxation into a solvable form. Relaxations will introduce conservatism, but at the same time retain stability and performance guarantees. In this brief, a new relaxation methodology is proposed, which allows the... 

We propose a compositional approach for the Partial Order Reduction (POR) in the state space generation of asynchronous timed actors. We define the concept of independent actors as the actors that do not send messages to a common actor. The approach avoids exploring unnecessary interleaving of executions of independent actors. It performs on a component-based model where actors from different components, except for the actors on borders, are independent. To alleviate the effect of the cross-border messages, we enforce a delay condition, ensuring that an actor introduces a delay in its execution before sending a message across the border of its component. Within each time unit, our technique... 

Statistical process control provides useful tools to improve the quality of multistage machining processes, specifically in continuous manufacturing lines, where product characteristics are measured at the final station. In order to reduce process errors, variation source identification has been widely applied in machining processes. Although statistical estimation and pattern matching-based methods have been utilized to monitor and diagnose machining processes, most of these methods focus on stage-by-stage inspection using complex models and patterns. However, because of the existence of high rate alarms and the complexity of the machining processes, a surrogate modelling is needed to solve... 

Measurements and sensing implementations impose certain cost in sensor networks. The sensor selection cost optimisation is the problem of minimising the sensing cost of monitoring a physical (or cyber-physical) system. Consider a given set of sensors tracking states of a dynamical system for estimation purposes. For each sensor assume different costs to measure different (realisable) states. The idea is to assign sensors to measure states such that the global cost is minimised. The number and selection of sensor measurements need to ensure the observability to track the dynamic state of the system with bounded estimation error. The main question we address is how to select the state... 

In this article, the dynamic responses of a Timoshenko beam subjected to a moving mass, and a moving sprung mass are analyzed. By making recourse to Hamilton's principle, governing differential equations for beam vibration are derived. By using the modal superposition method, the partial differential equations of the system are transformed into a set of Ordinary Differential Equations (ODEs). The resulted set of ODEs is represented in state-space form, and solved by means of a numerical technique. The accuracy of the results has been ascertained through comparing the results of our approach with those available from previous studies; moreover, a reasonable agreement has been obtained. The... 

Based on the first-order shear deformation plate theory, two approaches within the extended Kantorovich method (EKM) are presented for a bending analysis of functionally graded annular sector plates with arbitrary boundary conditions subjected to both uniform and non-uniform loadings. In the first approach, EKM is applied to the functional of the problem, while in the second one EKM is applied to the weighted integral form of the governing differential equations of the problem as presented by Kerr. In both approaches, the system of ordinary differential equations with variable coefficients in r direction and the set of ordinary differential equations with constant coefficients in θ direction... 

With the current focus on energy and environment, efficient integration of renewable energies, especially wind energy into power systems, is becoming essential. Furthermore, to fully capture wind potentials and to recognize the unique characteristics associated with wind energy in power systems adequacy analysis, a profound inquiry is required. In this way, this paper tries to establish a comprehensive analytical approach for reliability modeling of doubly-fed induction generator (DFIG)-based wind farms. First, the most impressive components of wind turbines are introduced. It then continues with integrating developed state space model of wind turbines and their production uncertainties,... 

With the current focus on energy and environment, efficient integration of renewable energies, especially wind energy into power systems, is becoming essential. Furthermore, to fully capture wind potentials and to recognize the unique characteristics associated with wind energy in power systems adequacy analysis, a profound inquiry is required. In this way, this paper tries to establish a comprehensive analytical approach for reliability modeling of doubly-fed induction generator (DFIG)-based wind farms. First, the most impressive components of wind turbines are introduced. It then continues with integrating developed state space model of wind turbines and their production uncertainties,... 

In today's world, control and navigation of autonomous underwater vehicles (AUVs) are quite challenging issues. In these fields, obtaining an identified dynamic model of AUV is a vital part. In this paper, a method for parameter estimation of an AUV planar model is proposed, which uses augmented state space technique and Square Root Transformed Unscented Kalman Filter (SR-TUKF) as an estimator. Furthermore, by modeling, misalignment between Inertial Measurement Unit (IMU) and Doppler Velocity Log (DVL) is estimated, simultaneously. Parameter identification is conducted using data of an AUV, equipped with Gyroscope, DVL and Encoder for measuring control inputs, in a planar maneuver. According... 

In this paper, we focus on the heavy-tailed stochastic signals generated through continuous-time autoregressive (CAR) models excited by infinite-variance α-stable processes. Our goal is to estimate the parameters of the continuous-time model, such as the autoregressive coefficients and the distribution parameters related to the excitation process for the α-stable CAR process with 0<α>2 based on the state-space representation. Likewise, we investigate the closed form expressions for the parameters of equivalent model in the discrete-time setting via regular samples of the process. We analyze the estimator based on the Monte Carlo simulations and illustrate the estimator consistency to the... 

A body insonified by a sound field is known to experience a steady force that is called the acoustic radiation force. In this paper, the method of wave function expansion is adopted to study the scattering and the radiation force function caused by a plane normal harmonic acoustic wave incident upon an arbitrarily thick-walled functionally graded cylindrical shell submerged in and filled with compressible ideal fluids. A laminate approximate model and the so-called state space formulation in conjunction with the classical transfer matrix (T-matrix) approach are employed to present an analytical solution based on the two-dimensional exact equations of elasticity. Two typical models,... 

Beside the major objective of providing congestion control, achieving predictable queuing delay, maximizing link utilization, and robustness are the main objectives of an active queue management (AQM) controller. This paper proposes an improved queue dynamic model while incorporating the packet drop probability as well. By applying the improved model, a new compensated PID AQM controller is developed for Transmission Control Protocol/Internet Protocol (TCP/IP) networks. The non-minimum phase characteristic caused by Padé approximation of the network delay restricts the direct application of control methods because of the unstable internal dynamics. In this paper, a parameter-varying dynamic... 

Rational function-based models have proved to be very efficient for accurate frequency-dependent modeling of power system components. These models are able to characterize the components terminal behaviours (analysing the admittance matrix) for nodal analysis. This provides a fast convergence and inherent stability to the solution routine of the model. This work presents a general framework for interfacing the dynamic phasor method to the rational models. That would be promising for the electromagnetic transient analysis (under harmonic distortion), in the frequency domain. Therefore, Y-element rational pole-residue models (employing the vector fitting method) are developed. Moreover, the... 

During this paper, a new simplified model is introduced for a neuron membrane, which is more or less, capable to mimic the dynamics of any specific physiological neuron membrane. This model is called Linear Oscillatory Neuron (LON) model, which is derived through special method of linearization applied to FitzHugh Nagumo[8] model in the neuron rest regime. As well, this linear model is terminated by a well known nonlinear system to achieve oscillatory and chaotic output, as it is observed in real neurons. Although some relatively exact models exist for special neurons, such as HH model [1,2] for giant axon of a squad (which is extracted through a Voltage clamp trial and curve fitting... 

A novel output feedback neural controller is presented in this paper for the implementation of sliding-mode control of dc/dc converters. The controller, which consists of a multilayer perceptron, has been trained in order to be robust for large variations of system parameters and state variables. Fast dynamic behavior is the other main advantage of the proposed controller, which allows realization of all beneficial features of the sliding-mode control technique. Other advantages of the controller are simplicity and low cost. Computer simulations have been carried out to investigate the effectiveness of the controller in voltage regulation for a relatively complex dc/dc converter topology of... 

The load current of three level/phase neutral point clamped rectifier could be expressed in two forms: the load current involving the current of capacitor C1, and the load current involving the current of capacitor C2. Using the Euler-Lagrange model based on the superposition law and the obtained load current, a new dual Lagrangian model of the rectifier is founded in this paper and then the two obtained nonlinear state space models are developed in dq0 reference frame. According to the new model, two positive definite Lyapunov function candidates are defined and a Lyapunov-based control is applied to the rectifier. Each of the function is utilized to control its corresponding output voltage...