Sharif Digital Repository

In this paper via a novel method of discretized continuous-time Kalman filter, the problem of synchronization and cryptography in fractional-order systems has been investigated in presence of noisy environment for process and output signals. The fractional-order Kalman filter equation, applicable for linear systems, and its extension called the extended Kalman filter, which can be used for nonlinear systems, are derived. The result is utilized for chaos synchronization with the aim of cryptography while the transmitter system is fractional-order, and both the transmitter and transmission channel are noisy. The fractional-order stochastic chaotic Chen system is then presented to apply the... 

In this paper the derivation of Kalman filter for discrete time-stochastic fractional system is investigated. Based on a novel cumulative vector form model for fractional systems, a general Kalman filter is introduced. The validity of the proposed method has been compared with a previously presented method via simulation results. It is shown that this method can be better applied for discrete time stochastic fractional systems with slower dynamics  

This work, based on the standard unscented Kalman filter (UKF), proposes a modified UKF for highly non-linear stochastic systems, assuming that the associated probability distributions are normal. In the standard UKF with 2n + 1 sample points, the estimated mean and covariance match the true mean and covariance up to the third order, besides, there exists a scaling parameter that plays a crucial role in minimising the fourth-order errors. The proposed method consists of a computationally efficient formulation of the unscented transform that incorporates N - 1, N ≥ 2, constant parameters to scale 2n(N - 1) + 1 sample points such that the 2Nth order errors are minimised. The scaling parameters... 

In this paper the derivation of Kalman filter for discrete time-stochastic fractional system is investigated. Based on a novel cumulative vector form model for fractional systems, a general Kalman filter is introduced. The validity of the proposed method has been compared with a previously presented method via simulation results. It is shown that this method can be better applied for discrete time stochastic fractional systems with slower dynamics  

The Stochastic Distribution Control (SDC) problem is a generalised form of the minimum variance control problem where non-Gaussian noise distributions are encountered. The problem has been previously solved using two alternative approaches. When it is assumed that the output Probability Distribution Function (PDF) is measurable, then a parameterized controller is obtained. If on the other hand this assumption is removed (which corresponds to most practical cases), then the controller found is no longer parameterisable (i.e. it is a control action sequence). Both these approaches have thus far been solved using local Newtonian methods. In this paper a third alternative is presented which... 

In analyzing the lifetime properties of a coherent system, the concept of "signature" is a useful tool. Let T be the lifetime of a coherent system having n iid components. The signature of the system is a probability vector s=(s1, s2,., sn), such that s i=P(T=Xi:n), where, Xi:n, i=1, 2,., n denote the ordered lifetimes of the components. In this note, we assume that the system is working at time t>0. We consider the conditional signature of the system as a vector in which the ith element is defined as pi(t)=P(T=Xi: n|T>t) and investigate its properties as a function of time  

TRISO particles are the specific features of HTTR and generally HTGR reactors. Their heterogeneity and random arrangement in graphite matrix of these reactors create a significant modeling challenge. In this study, an algorithm is proposed for modeling random arrangement of TRISO particles in the fuel compacts of HTTR. The effect of this arrangement on criticality calculations, i.e. effective multiplication factor and critical position of control rods, is then compared with regular arrangement. Regular arrangement was modeled by positioning each TRISO as a fixed sphere in the center of a cubic lattice and subsequently, each fuel compact was filled with around 13,000 (approximate number of... 

A new heuristic controller, called Continuous Ant Colony Controller, is proposed for nonlinear stochastic systems. The new controller formulates the states estimation and model predictive control problems as a single stochastic dynamic optimization problem and utilizes a colony of virtual ants to find and track the best state estimation and the best control signal. For this purpose an augmented state space is defined. An integrated cost function is also defined to evaluate the ants within the state space. This function minimizes simultaneously the state estimation error, tracking error, control effort and control smoothness. Ants search the augmented state space dynamically in a similar... 

A new heuristic filter, called firefly filter, is proposed for state estimation of nonlinear stochastic systems. The new filter formulates the state estimation problem as a stochastic dynamic optimization and utilizes the firefly optimization algorithm to find and track the best estimation. The fireflies search the state space dynamically and are attracted to one other based on the perceived brightness. The performance of the proposed filter is evaluated for a set of benchmarks and the results are compared with the well-known filters like extended Kalman filter and particle filter, showing improvements in terms of estimation accuracy. © 2016 IEEE  

A new heuristic controller, called the continuous ant colony controller, is proposed for non-linear stochastic Gaussian/non-Gaussian systems. The new controller formulates the state estimation and the model predictive control problems as a single stochastic dynamic optimization problem, and utilizes a colony of virtual ants to find and track the best estimated state and the best control signal. For this purpose, an augmented state space is defined. An integrated cost function is also defined to evaluate the points of the augmented state space, explored by the ants. This function minimizes simultaneously the state estimation error, tracking error, control effort and control smoothness. Ants... 

Available transfer capability (ATC) provides important information for power marketers and planning sectors in restructured power systems. The stochastic nature of power system behaviour, however, made ATC determination a difficult and complicated task. A stochastic framework has been established for ATC calculation with implication of uncertainties in transmission failures, hourly peak loads and system cascading collapse. The proposed ATC calculation framework is based on parametric bootstrap technique which enables generating random samples of system operating condition with uncertainty at a predefined confidence interval. The IEEE RTS-96 network is employed to demonstrate the... 

In this paper, for one-dimensional stochastic linear fractional systems in terms of the Riemann-Liouville fractional derivative, the optimal control is derived. It is assumed that the state is completely observable and all the information regarding this is available. The formulation leads to a set of stochastic fractional forward and backward equation in the Riemann-Liouville sense. The proposed method has been checked via some numerical simulations which show the effectiveness of the fractional stochastic optimal algorithm  

We investigate the problem of reliable communication in the presence of active adversaries that can tamper with the transmitted data. We consider a legitimate transmitter-receiver pair connected over multiple communication paths (routes). We propose two new models of adversary, a 'memoryless' and a 'foreseer' adversary. For both models, the adversaries are placing themselves arbitrarily on the routes, keeping their placement fixed throughout the transmission block. This placement may or may not be known to the transmitter. The adversaries can choose their best modification strategy to increase the error at the legitimate receiver, subject to a maximum distortion constraint. We investigate... 

The problem of finding the expected shortest path in stochastic networks, where the presence of each node is probabilistic and the arc lengths are random variables, have numerous applications, especially in communication networks. The problem being NP-hard we use an ant colony system (ACS) to propose a metaheuristic algorithm for finding the expected shortest path. A new local heuristic is formulated for the proposed algorithm to consider the probabilistic nodes. The arc lengths are randomly generated based on the arc length distribution functions. Examples are worked out to illustrate the applicability of the proposed approach  

This paper proposes a novel technique to prove a one-shot version of achievability results in network information theory. The technique is not based on covering and packing lemmas. In this technique, we use a stochastic encoder and decoder with a particular structure for coding that resembles both the ML and the joint-typicality coders. Although stochastic encoders and decoders do not usually enhance the capacity region, their use simplifies the analysis. The Jensen inequality lies at the heart of error analysis, which enables us to deal with the expectation of many terms coming from stochastic encoders and decoders at once. The technique is illustrated via four examples: point-to-point... 

Although fluctuations in the waiting time series have been studied for a long time, some important issues such as its long-range memory and its stochastic features in the presence of nonstationarity have so far remained unstudied. Here we find that the "waiting times" series for a given increment level have long-range correlations with Hurst exponents belonging to the interval 1/2