Sharif Digital Repository

Process Fault Diagnosis (PFD) involves interpreting the current status of the plant given sensor readings and process knowledge. There has been considerable work done in this area with a variety of approaches being proposed for PFD. Neural networks have been used to solve PFD problems in chemical processes, as they are well suited for recognizing multi-dimensional nonlinear patterns. In this work, the use of Hierarchical Artificial Neural Networks (HANN) in diagnosing the multi-faults of a chemical process are discussed and compared with that of Single Artificial Neural Networks (SANN). The lower efficiency of HANN, in comparison to SANN, in PFD is elaborated and analyzed. Also, the concept... 

In this paper, an object oriented method is developed for generation, optimization and management of a hydrocarbon (CxHy) pyrolysis reaction network using a Bond-Electron (BE) matrix. A computer program was developed using C++ language. This program can provide and generate a pyrolysis reaction network for a wide range of hydrocarbons, including alkanes, olefins, diolefins, cyclic and aromatic compounds, using the linear notation structure of the reactant species. Furthermore, the reaction patterns and pruning methods are considered and a new method is presented for identification of reactants and products. The structural identification of species contained in the network allows one to... 

pH control is known to be a challenging problem due to its highly nonlinear nature. Several control strategies are proposed for controlling pH processes among which is the strong acid equivalent scheme. Although this technique is robust to modeling error, the controller performance is degraded if the titration curve undergoes large changes. To overcome this problem, two control schemes that are based on the strong acid equivalent strategy and that use the multiple models, switching, and tuning approach are proposed in this work. For modeling, both fixed and adaptive models are considered. An experimental setup is used to evaluate the performance of the proposed scheme. The effectiveness of... 

A Real-Time Optimization (RTO) strategy incorporating the fuzzy sets theory is developed, where the problem constraints obtained from process considerations are treated in fuzzy environment. Furthermore, the objective function is penalized by a fuzzified form of the key process constraints. To enable using conventional optimization techniques, the resulting fuzzy optimization problem is then reformulated into a crisp programming problem. The crisp programming problem is solved using both Sequential Quadratic Programming (SQP) and Heuristic Random Optimization (HRO) techniques for comparison purposes. The proposed fuzzy RTO strategy is demonstrated via the Tennessee Eastman benchmark process,... 

In this paper, two control charts based on the generalized linear test (GLT) and contingency table are proposed for Phase-II monitoring of multivariate categorical processes. The performances of the proposed methods are compared with the exponentially weighted moving average-generalized likelihood ratio test (EWMA-GLRT) control chart proposed in the literature. The results show the better performance of the proposed control charts under moderate and large shifts. Moreover, a new scheme is proposed to identify the parameter responsible for an out-of-control signal. The performance of the proposed diagnosing procedure is evaluated through some simulation experiments. © 2017 Taylor & Francis... 

In some quality control applications, quality of a product or a process can be characterized by a profile defined as a functional relationship between a response variable and one or more explanatory variables. Many researchers have contributed to the development of linear and nonlinear profiles to monitor a process or product. However, less work has been devoted to the development of process capability indices in profile monitoring to evaluate process performance with respect to specification limits. This paper presents a process capability analysis when the quality characteristic of interest is represented by a linear profile. Simulation analyses along with a real case study in leather... 

Model-based pH control is a difficult problem due to its inherent nonlinearity and time-varying characteristics. This is specially the case when the pH regulation of streams consisting hundreds of constituents with varying concentrations is desired. The pH process can be modeled by using conservation laws and neutrality condition. An alternative to this mechanistic modeling is using nonlinear empirical modeling such as fuzzy modeling. This paper proposes a new approach of fuzzy modeling of titration curves, which can be used for control purposes. The Takagi-Sugeno model was used for the modeling of titration curve. Two control algorithms, which are designed based on the titration curve,... 

In this paper, we study passivity in dynamic manipulation of active objects. Active object is a concept covering a variety of objects, which are not rigid and need to be controlled during manipulation process. In this work, we use multi-link mechanisms with sufficient actuators to be controlled as object and a series of simple 1-DoF passive manipulators to perform such a process. Control of the object, dynamic and motion planning of the system, and stability in presence of impact are significant issues in this study  

In this work, we study a kind of manipulation process during which we deal with active objects. An active object is a concept covering a variety of objects that are not rigid and need to be controlled during the manipulation process. Here, we use a multi-link mechanism with active motors (actuator) as the object and a series of simple planar manipulators to perform the manipulation process. Dynamic, control, motion planning, and stability at the presence of impact are the most important challenges in this work  

In this paper, a new model predictive controller is introduced to control a power unit process with three inputs and three outputs. This method is proposed to reduce the complexity of the required computation. In fact, the presented controller ensures achieving an acceptable performance in the presence of noise and disturbances and reduces the volume of calculations to control a complex and nonlinear boilerturbine process. The simulation results indicate that the implementation of the proposed controller requires less computing time while the performance degradation is not more than five percent  

A dynamical hybrid observer is proposed for online reconstruction of the active mode and continuous states of Pressure Swing Adsorption (PSA) processes as an integral part of a hybrid control system. A mode observer is designed for estimation of the active mode, and the continuous spatial profiles are estimated by a Distributed and Decentralized Switching Kalman Filter. The proposed hybrid observer has been applied, in silico, for a two-bed, six-step PSA process. The active mode of the process along with the continuous spatial profiles of its adsorption beds have been estimated quite accurately based on very limited number of noise corrupted temperature and pressure measurements. © 2017  

In this article, we adopt the change point approach to monitor the generalized linear profiles in phase II Statistical process control (SPC). Generalized linear profiles include a large class of profiles defined in one framework. In contrast to the conventional change point approach, we adopt the Rao score test rather than the likelihood ratio test. Simulated results show that our approach has a good performance over any possible single step change in process parameters for two special cases of generalized linear profiles, namely Poisson and binomial profiles. Some diagnostic aids are also given and a real example is introduced to shed light on the merits of our approach in real... 

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... 

In this paper, two nonlinear observer based controllers for temperature control of a continuous stirred tank reactor in which a special class of parallel exothermic reactions take place are proposed. A reduced order nonlinear observer is constructed to estimate the concentration in the reactor. The observer is coupled with two nonlinear controllers, designed based on two well-known techniques, namely input-output linearization and backstepping for controlling the reactor temperature. For dampening the effect of observer error dynamics, a compensating term is used in each control law. The asymptotical stability of the closed-loop system is shown by the Lyapunov's stability theorem. The... 

This effort attempts to study the change point problem in the area of non-linear profiles. A method based on Artificial Neural Networks (ANN) is proposed for estimating the real time of a single step change. The feature vector of the proposed Multi-Layer Perceptron (MLP) is based on Z and control chart statistics for nonlinear profiles. The merits of the proposed estimator are evaluated through simulation experiments. The results show that the estimator provides an accurate estimate of the single step change point in non-linear profiles in the selected case problem. © 2021, The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division 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... 

The current of outgoing feeders are very important data transmitted over SCADA system. Monitoring of these currents can help dispatching engineers to detect abnormality in energy consumption trend and minor faults in distribution network. Statistical process control (SPC) is one of the capable approaches which can be used for this purpose. Statistical process control is based on categorizing variations into assignable causes and random causes. In current paper we described the methods which were used for finding assignable causes in load trend and short time load variation in Alborz province power distribution company pilot project. Although this approach is not developed completely and some... 

Application of advanced process control methods in a chemical plant requires a model which represents the transient behaviour of the plant. However, only a few plant-wide identification methods have been proposed for chemical processes. In this paper, an objectoriented process identifier (OPI) framework has been introduced for plant-wide identification to show how using object-oriented design can provide a general plant-wide modelling framework for various systems including chemical processes. The interactions between units are considered in plant-wide identification methods. As a result, the obtained models can predict the system behaviour in new operating conditions better than those...