Sharif Digital Repository

Statistical process control methods for monitoring processes with multivariate measurements in both the product quality variable space and process variable space are considered in this paper. Some processes, however, are better characterized by a profile or a function of quality variables. For each profile, we assume that a collection of data on the response variable along with the values of the corresponding quality variables is measured. While the linear function is the simplest, it occurs frequently that many of the nonlinear functions may be transferred to linear functions easily. This paper proposes a control chart based on the generalized linear test (GLT) to monitor coefficients of... 

Four nonlinear Model Reference Adaptive Impedance Controllers are introduced, tested, and compared for the control of the robot impedance with uncertainties in model parameters. The intended application area is human-robot interactions (HRI), particularly rehabilitation robots and haptic interfaces. All of the controllers make the closed-loop dynamics of the robot similar to the reference impedance model besides providing asymptotic tracking of the impedance model for the robot end-effector in Cartesian coordinates. The tracking and global stability are proved using Lyapunov stability theorem. Based on the simulations and experiments on a two-DOFs robot, the effectiveness of the proposed... 

Evaluation of a project and its contractors has considerable importance in gas well-drilling projects due to their high investments and worth. In this paper, the quality of some gas well-drilling projects is analyzed in order to evaluate and grade project tasks. A neuro-fuzzy network is utilized to learn the grading process and generate models. To select among these models, a ranking method, namely technique for order of preference by similarity to ideal solution (TOPSIS) is employed. During seven gas well-drilling projects, 77 tasks are studied based on quality practitioners[U+05F3] points of view. After generating the primary models, three indices namely, root mean square error (RMSE),... 

Purpose: The purpose of this paper is to apply Poisson generalized linear model (PGLM) with log link instead of multinomial logistic regression to monitor multinomial logistic profiles in Phase I. Hence, estimating the coefficients becomes easier and more accurate. Design/methodology/approach: Simulation technique is used to assess the performance of the proposed algorithm using four different control charts for monitoring. Findings: The proposed algorithm is faster and more accurate than the previous algorithms. Simulation results also indicate that the likelihood ratio test method is able to detect out-of-control parameters more efficiently. Originality/value: The PGLM with log link has... 

An adaptive input-output linearization method for general nonlinear systems is developed without using states of the system. Another key feature of this structure is the fact that, it does not need model of the system. In this scheme, neurolinearizer has few weights, so it is practical in adaptive situations. Online training of neurolinearizer is compared to model predictive recurrent training. Relationships between this controller and neural network based model reference adaptive controller are established. A CSTR reactor and pH control in a neutralization process illustrate performance of this method. Simulation studies show a superior performance with respect to a PI controller  

A predictive functional controller based on ARMarkov model structure has been designed to control welding current and arc voltage in a GMAW process. The closed loop system performance is investigated through computer simulations and is compared by those achieved from implementing two commonly used controllers i.e. PI and feedback linearization based PID. The local stability of the closed loop system is analyzed in the presence of uncertainties in the linearized model of the process as well as the control parameters. Finally it is shown that the proposed controller performs like a PI controller along with a pre-filter compensator  

The Phase I applications of the statistical profile monitoring have recently been extended to the case when the response variable is binary. We are motivated to undertake the current research in an attempt to try to provide a unified framework for the Phase I control in the context of statistical profile monitoring that can be used to tackle a large class of response variables, such as continuous, count, or categorical response variables. The unified framework is essentially based on applying the change point model to the class of generalized linear models. The proposed Phase I control chart is assessed and compared with the existing charts under binomial and Poisson profiles. Some... 

Inference and Estimation in Missing Information (MI) scenarios are important topics in Statistical Learning Theory and Machine Learning (ML). In ML literature, attempts have been made to enhance prediction through precise feature selection methods. In sparse linear models, LASSO is well-known in extracting the desired support of the signal and resisting against noisy systems. When sparse models are also suffering from MI, the sparse recovery and inference of the missing models are taken into account simultaneously. In this paper, we will introduce an approach which enjoys sparse regression and covariance matrix estimation to improve matrix completion accuracy, and as a result enhancing... 

In this paper, different model predictive control synthesis frameworks are examined for DCDC quasi-resonant converters in order to achieve stability and desired performance. The performances of model predictive control strategies which make use of different forms of linearized models are compared. These linear models are ranging from a simple fixed model, linearized about a reference steady state to a weighted sum of different local models called multi model predictive control. A more complicated choice is represented by the extended dynamic matrix control in which the control input is determined based on the local linear model approximation of the system that is updated during each sampling... 

A downscaling model capable of explaining the temporal and spatial variability of regional hydroclimatic variables is essential for reliable climate change studies and impact assessments. This study proposes a novel statistical approach based on generalized hierarchical linear model (GHLM) to downscale precipitation from the outputs of general circulation models (GCMs) at multiple sites. GHLM partitions the total variance of precipitation into within- and between-site variability allowing for transferring information between sites to develop a regional downscaling model. The methodology is demonstrated by downscaling precipitation using the outputs of eight GCMs in Lake Urmia basin in... 

During the milling process, self-excited vibration or chatter adversely affects tool life, surface quality and productivity rate. In this paper, nonlinear cutting forces of milling process are considered as a function of chip thickness with a complete third order polynomial (instead of the common linear dependency). An optimal control strategy is developed for chatter suppression of the system described through nonlinear delay differential equations. Counterbalance forces exerted by actuators in x and y directions are the control inputs. For optimal control problem, an appropriate performance index is defined such that the regenerative chatter is suppressed while control efforts are... 

In this study, a conceptual framework is postulated to mathematically evaluate and ascertain the hypothesised relationship that perceived value and interactivity has with customer dissatisfaction issues. Then, the relationship between customer satisfaction issues and loyalty and customer acquisition, will be tested to enhance customer satisfaction and loyalty. For the qualitative part of the research, an interview survey was conducted of 40 employees at the Fremantle port of Western Australia and the collected data was analysed using NVivo. In the second data collection phase, a survey questionnaire was distributed to 60 port customers. Using data envelopment analysis (DEA), the important... 

Digital documents are usually degraded during the scanning process due to the contents of the backside of the scanned manuscript. This is often caused by the show-through effect, i. e. the backside image that interferes with the main front side picture due to the intrinsic transparency of the paper. This phenomenon is one of the degradations that one would like to remove especially in the field of Optical Character Recognition (OCR) or document digitalization which require denoised texts as inputs. In this paper, we first propose a novel and general nonlinear model for canceling the show-through phenomenon. A nonlinear blind source separation algorithm is used for this purpose based on a new... 

With the significant role that warehouse plays in connection to suppliers, distributors, and clients, and considering the costliness of storage systems, efforts have focused on the reduction of procedural expenses. Among the most significant expenses, one involves the distance traveled by operators or S/R machinery for the selection of ordered items; the common solution to which has been through the classification of stored items. Previous articles have focused on linear solutions to the abovementioned problem, such as P-Median. This article shall focus on the problems arising from the said solution, and instead a non-linear method proposed. Further, a heuristic algorithm is produced for the... 

In this study, flocking of multi-agent systems with virtual leader and linear dynamics is investigated. It is assumed that the dynamics of agents in each dimension is represented by a general second-order linear model. The proposed control protocol is composed of two terms, one for feed backing each agent's states and one for cooperative control. At first, the flocking problem of multi-agent systems with identical agents is discussed and then the proposed protocol is generalised to flock heterogeneous multi-agent systems. Under the proposed algorithm, the velocity convergence of whole group to a velocity of virtual leader is guaranteed while the connectivity of network is preserved and... 

This paper presents an attempt to control the chaotic behavior of Rayleigh-Bénard convection system in weakly elastic fluids. In this article, a nonlinear model is presented which fundamentally refers to a model introduced by Khayat. The nonlinear model has chaotic behavior which is controlled by using sliding mode method. In the presence of uncertainty for some parameters of the model, a controller is designed to stabilize the dynamic of the system on the desired trajectory. Different simulation results are presented to demonstrate the effectiveness of the designed controller in tracking different desired trajectories. ©2009 IEEE  

Digital documents are usually degraded during the scanning process due to the printings existing on the backside of the scanning manuscript. This is often caused by the so called show-through effect, the image that interferes with the main picture due to the intrinsic opacity of the paper. This phenomenon is on type of degradation that one would like to remove. In this paper, we propose a novel and general nonlinear model for show-through phenomenon. A nonlinear blind source separation (BSS) algorithm is used for this particular application in a new recursive and extendible structure for compensating show-through. Finally, we introduce a new structure for removing the show-through and the... 

In this paper we propose a new method for estimating the mixing matrix, A, in the linear model X = AS, for the problem of underdetermined Sparse Component Analysis (SCA). Contrary to most existing algorithms, in the proposed algorithm there may be more than one active source at each instant (i.e. in each column of the source matrix S), and the number of sources is not required to be known in advance. Since in the cases where more than one source is active at each instant, data samples concentrate around multidimensional subspaces, the idea of our method is to first estimate these subspaces and then estimate the mixing matrix from these estimated subspaces. ©2007 IEEE