Sharif Digital Repository

Some of the most important classes of watermark detection methods in image watermarking are correlation-based algorithms. In these methods usually a pseudorandom noise pattern is embedded in the host image. The receiver can regenerate this pattern by having a key that is the seed of a random number generator. After that if the correlation between this pattern and the image that is assumed to have the watermark is higher than a predefined threshold, it means that the watermark exists and vice versa. Here, we show the advantage of using the Julian set patterns as a watermark, instead of the commonly used pseudorandom noise pattern. Julian set patterns can be regenerated in receiver with few... 

Vector control induction motor drives are particularly sensitive to the variation of motor parameters. As a consequence, the field orientation is missed, leading to substantial degradation of performance. The performance of traction motors can be even more degraded by the substantial core loss due to their high supply frequency. In this paper, a flux observer using combined voltage and current model is presented. The influence of the core loss resistance is considered in motor models. This control system is robust against simultaneous variations of the stator resistance, rotor resistances, as well as the mismatch of the equivalent stator core-loss resistance, yielding a globally stable... 

A hot gas generator is a compact heat exchanger that produces high temperature or enthalpy gases. This paper presents two methods for controlling the system. The first one is an adaptive sliding mode controller that is a Lyapunov based method and proposed to confront the dynamic modeling deficiencies and system uncertainties. The second one is a linear adaptive controller that gives a new attractive ability to the system which can track a complicated requested path. Each of the presented controllers has some capabilities that may be preferred to other. In this paper, these methods are extensively compared by several transient inputs. On the other hand, since heat exchangers are typically... 

Control of the air-handling units (AHU) is required to maintain satisfactory comfort conditions with low energy consumption. In the case of failure in sensor fusion systems of AHUs, full-order observers can be used as the supportive tool to provide an acceptable estimation of state variables. In this paper, a multivariable nonlinear model of the AHU is considered in the presence of uncertainties. The indoor temperature and relative humidity are controlled via manipulation of valve positions of air and cold water flow rates. In proposed hybrid control system, full and minimum-order observers are designed for the estimation of indoor temperature and relative humidity. Also, a regulator for... 

In this paper, an adaptive critic-based neurofuzzy controller is presented for water level regulation of nuclear steam generators. The problem has been of great concern for many years as the steam generator is a highly nonlinear system showing inverse response dynamics especially at low operating power levels. Fuzzy critic-based learning is a reinforcement learning method based on dynamic programming. The only information available for the critic agent is the system feedback which is interpreted as the last action the controller has performed in the previous state. The signal produced by the critic agent is used alongside the backpropagation of error algorithm to tune online conclusion parts... 

This paper presents an adaptive delay compensator (ADC) on the basis of the latest development in wide-area measurement system (WAMS) to cater to varying latencies. The proposed compensator can effectively reciprocate the phase deviation resulting from varying delays to improve the performance of central wide-area damping controller (WADC). The greatest challenge to continuous delay compensation is the uncertainty regarding the inherent robustness of the central controller. The proposed technique provides an opportunity to epitomize the uncertainty retrieved from phase compensated delay. Next, taking the uncertainty into consideration, the mixed H2H∞ synthesis technique is adopted for the... 

This paper develops methodology and technique tor the design, analysis, and impie mentation of an adaptive generalized predictive controller (AGPC) for Active Queue Management in TCP Networks. The TCP/AQM dynamic is modeled experimentally as a second-order system with a time delay where its parameters are estimated using the standard gradient algorithm. Based on this model, an AGPC is designed to gain the set-point tracking and robustness. AGPC, as a queue-based control mechanism, responds quickly to traffic changes, thus allowing for high utilization and small loss. We illustrate our results using ns-2 simulations and demonstrate the practical impact of adaptive model reference control on... 

This study investigates the asymptotic swarm stabilisation of fractional-order swarm systems in the presence of two different kinds of model uncertainties and external disturbances while the upper bound of the uncertainties is a linear function of pseudo-states norms with unknown coefficients. To this end, first a fractional-integral sliding manifold is constructed and then an adaptive-robust sliding mode controller is designed to guarantee the asymptotic swarm stability in a fractional-order linear time-invariant swarm system. The stability analysis of the proposed control system is done based on the Lyapunov stability theorem. Using the proposed controller, the coefficients of the upper... 

In most approaches to adaptive robust control design for manipulators, a constant upper bound is considered for unmodeled dynamics. However, experiments show that the nature of the control input affects the magnitude of the unmodeled dynamics. For example, in an almost rigid manipulator where the mechanical flexibilities are considered as unmodeled dynamics, high frequency components of the input torque which are resulted form non-smooth control laws, can themselves excite system flexibilities. In this paper, we consider different characterizations of the unmodeled dynamics to take into account the effect of control input signal on the unmodeled dynamics. Simulation results illustrate the... 

In this paper, a robust control design strategy is introduced to synchronize two different chaotic systems. The controller is based on particle swarm optimization (PSO). Particle swarm optimization is a well-known evolutionary optimization algorithm inspired by organism behavior of birds flocking and fish schooling. Our control approach is based on defining a suitable cost function in such a way that minimizing it guarantees the control of system. Due to the nature of PSO algorithm, the designed controller is strongly robust. It is shown that the proposed controller can overcome the parameter uncertainty without any extra information about the system. Comparison of proposed method with... 

An adaptive wide-area damping controller (WADC) scheme based on gain scheduling (GS) technique and decision tree (DT) approach is presented. For the predefined operating scenarios, several robust controllers are designed, so that each controller performs well within a certain range of load/generation variation and contingencies. Considering the best acting controller in each operating condition as the target of classification, several DTs are trained using stage-wise additive modeling by multiclass exponential loss function (SAMME). The weighted combination of DTs is referred to as additive model DT (AMDT) that is used to interpolate the controller coefficients from phasor measurement unit... 

This letter presents a unified framework for the design of prescribed-time controllers under time-varying input and state constraints for normal-form unknown nonlinear systems with uncertain input gain. The proposed approach is based on a time-domain mapping method by which any infinite-time system can be corresponded to a prescribed-time system and vice versa. It is shown that the design of a constrained nonasymptotic prescribed-time controller can be reduced to the asymptotic control design for an associated constrained infinite-time system. Faà di Bruno’s formula and Bell polynomials are used for a constructive representation of the associated infinite-time system. The presented results... 

This letter presents a unified framework for the design of prescribed-time controllers under time-varying input and state constraints for normal-form unknown nonlinear systems with uncertain input gain. The proposed approach is based on a time-domain mapping method by which any infinite-time system can be corresponded to a prescribed-time system and vice versa. It is shown that the design of a constrained nonasymptotic prescribed-time controller can be reduced to the asymptotic control design for an associated constrained infinite-time system. Faà di Bruno's formula and Bell polynomials are used for a constructive representation of the associated infinite-time system. The presented results... 

All realistic Multi-Criteria Decision Making (MCDM) problems face various kinds of uncertainty. Since the evaluations of alternatives with respect to the criteria are uncertain they will be assumed to have stochastic nature. To obtain the uncertain optimism degree of the decision maker fuzzy linguistic quantifiers will be used. Then a new approach for fuzzy-stochastic modeling of MCDM problems will be introduced by merging the stochastic and fuzzy approaches into the OWA operator. The results of the new approach, entitled FSOWA, give the expected value and the variance of the combined goodness measure for each alternative. Robust decision depends on the combined goodness measures of... 

Most of industrial applications of statistical process control involve more than one quality characteristics to be monitored. These characteristics are usually correlated, causing challenges for the monitoring methods. These challenges are resolved using multivariate quality control charts that have been widely developed in recent years. Nonetheless, multivariate process monitoring methods encounter a problem when the quality characteristics are of the attribute type and follow nonnormal distributions such as multivariate binomial or multivariate Poisson. Since the data analysis in the latter case is not as easy as the normal case, more complexities are involved to monitor multiattribute... 

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... 

A new approach is developed in this paper to detect general mean shifts of multivariate quality control systems and to determine the quality characteristic(s) responsible for the shift. This approach takes advantage of both a decomposition method and an EWMA-based control statistics that are employed for multivariate normal distributions. In order to evaluate the performance of the proposed methodology, simulation studies are provided to estimate the in- and out-of-control average run lengths under different mean and variance shift scenarios. Simulation experiments are also given to compare the performances of the proposed procedure with the ones of the well-known MEWMA and MCUSUM methods.... 

An economic-statistical design with multiple assignable causes following exponential distribution is presented in this paper for linear profiles. For this purpose, a tri-objective optimization model is proposed to minimize the cost with desired statistical performances. Average Run Length (ARL) as the primary statistical measure is employed for the appraisal of the designed linear profiles. The first objective to be minimized is a cost function that models the implementation cost in different states. The second objective is to maximize ARL or the in-control average run-length of the monitoring scheme. The third objective to be minimized is ARL 1 or the out-of-control average run-length of... 

Existence of uncertainties in the model of real-world plants can trouble the control system designer in achievement of control objectives in control of such plants. In modeling of these plants by benefiting from fractional order models, one of the most commonplace types of uncertainties is the order uncertainty. This paper deals with presenting a method for tuning fractional order PI (FOPI) controllers to be used in control of plants, modeled by fractional order transfer functions consisting of a fractional order pole in addition to a time delay, such that the control system is robust against order variations. By the proposed tuning method, values of phase margin and gain crossover frequency... 

In this paper, a new control scheme is proposed for Phase-II monitoring of simple linear profiles in multistage processes. In this scheme, an approach based on the U transformation is first applied to remove the effect of the cascade property involved in multistage processes. Then, a single max-EWMA-3 control statistic is derived based on the adjusted parameter estimates for simultaneous monitoring of all the parameters of a simple linear profile in each stage. Not only is the proposed scheme able to detect both increasing and decreasing shifts but it also has the feature of identifying the out-of-control parameter responsible for the source of process shift. Using extensive simulation...