Sharif Digital Repository

One of the main shortcomings, caused by high penetration of wind power, is intermittency of generation. For integrating high penetration of wind power, the frequency regulation and the transactive control systems are modified to be sufficiently resilient against fluctuations of wind power and malicious cyber threats. Here, a hierarchical state-space model is presented for the frequency regulation and the transactive control systems in a smart grid environment. To achieve a resilient control, a framework based on cloud computing is proposed for the communication network. Benefits and challenges of the cloud-based framework are also described in this paper. To optimize the operation of the... 

In the present study, a simple analytical method is introduced for determination of natural frequencies of generally laminated conical and cylindrical shells with arbitrary boundary conditions. The governing equations of motion employed are those of thin-walled shell theory of Donnell. The free-vibration equations are solved using state space method and series solution in meridional direction. The results are compared and validated with the available especial results in the literature. The effects of bending-stretching coupling, semi-vertex angle, meridional length, shell thickness, fiber directions of composite plies, and lamination sequences on the natural frequency of conical and... 

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... 

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... 

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... 

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... 

The use of Model Aided Inertial Navigation (MAIN) during the landing of an Unmanned Aerial Vehicle (UAV) is investigated. A new MAIN algorithm is proposed, which is fast and accurate enough to be used in automatic landing. In this algorithm, the six Degree of Freedom (6DoF) model of the UAV is tightly coupled with the inertial navigation system; thus, the 6DoF model acts as an aiding system for the INS and vice versa. In the last parts of the landing phase in proximity of Earth, the proposed algorithm also estimates and removes the Ground Effect (GE) uncertainties and provides the height controller with a realistic model. An adaptive controller based on a parametric state-space model is used... 

One of the main shortcomings, caused by high penetration of wind power, is intermittency of generation. For integrating high penetration of wind power, the frequency regulation and the transactive control systems are modified to be sufficiently resilient against fluctuations of wind power and malicious cyber threats. Here, a hierarchical state-space model is presented for the frequency regulation and the transactive control systems in a smart grid environment. To achieve a resilient control, a framework based on cloud computing is proposed for the communication network. Benefits and challenges of the cloud-based framework are also described in this paper. To optimize the operation of the... 

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... 

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... 

As radar signals propagate above the ocean surface to determine the trajectory of a target, the signals that are reflected directly from the target arrive at the receiver along with indirect signals reflected from the ocean surface. These unwanted signals must be properly filtered; otherwise, their interference may mislead the signal receiver and significantly degrade the tracking performance of the radar. To this end, we propose a low-elevation target tracking mechanism considering the specular and diffuse reflection effects of multipath propagation over the ocean surface simultaneously. The proposed mechanism consists of a state-space model and a particle filtering algorithm and promises... 

Overwhelming number of control laws has been studied for control of robot manipulators with rigid links and joints. However controllers designed under this assumption may not accurately control the manipulator link due to visco-elastic properties that appear in the link behavior. In this study, a novel approach for robust control of a single-link manipulator is presented to force the link to have rigid motions, while it has visco-elastic behavior. In this regard, initially robot dynamics is extracted, followed by the design of four appropriate controllers through the loop-shaping approach. The obtained model is first represented in state space, however later converted to transfer function... 

Stability has been one of the major issues of time-domain numerical methods used for solving Maxwell equations. This problem takes a more severe form when additional algorithms are introduced to the computation domain (e.g. Absorbing Boundary Conditions-ABCs). There are a number of methods for investigating the stability of a simulation. In this article the problem of stability of ABCs, has been tackled through a control system's state-space point of view. Thus, occurrence of instability in a simulation can be predicted. © 2007 IEEE  

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... 

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... 

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... 

This paper deals with the consensus problem in an uncertain multi-agent system whose agents communicate with each other through a weighted undirected (primary) graph. The considered multi-agent system is described by an uncertain state-space model in which the involved matrices belong to some matrix boxes. As the main contribution of the paper, a unified optimization-based framework is proposed for simultaneously reducing the weights of the edges of the primary communication graph (optimizing the network topology) and synthesizing a controller such that the consensus in the considered uncertain multi-agent system is ensured with an adjustable convergence rate. Considering the NP-hardness... 

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... 

Actor-based modeling is known to be an appropriate approach for representing concurrent and distributed systems. Rebeca is an actor-based language with a formal foundation, based on an operational interpretation of the actor model. We develop a front-end tool for translating a subset of Rebeca to SMV in order to model check Rebeca models. Automated modular verification and abstraction techniques are supported by the tool  

It is known that discrete-time controllers, whose state matrices have no non-integer element, are beneficial in homomorphic based encrypted control systems. Nevertheless, it has been recently shown that possessing state matrices with integer elements usually yields unstable discrete-time controllers. In this note, we investigate the problem from a non-minimality perspective. It is shown that non-minimal realizations, in comparison to minimal ones, can theoretically provide a wider framework to obtain controllers having state matrices with integer elements. However, in the case of dealing with BIBO stable controllers, this framework cannot preserve internal stability. But, benefiting from the...