In all process industries, the process variables like flow, pressure, level, concentration
and temperature are the main parameters that need to be controlled in both set point
and load changes.
A control system of propylene glycol production in a non isothermal (CSTR) was
developed in this work where the dynamic and control system based on basic mass
and energy balance were carried out.
Inlet concentration and temperature are the two disturbances, while the inlet
volumetric flow rate and the coolant temperature are the two manipulations. The
objective is to maintain constant temperature and concentration within the CSTR.
A dynamic model for non isothermal CSTR is described by a first order plus dead
time (FOPDT).
The conventional PI and PID control were studied and the tuning of control
parameters was found by Ziegler-Nichols reaction curve tuning method to find the
best values of proportional gain (Kc), integral time ( I) and derivative time ( D).
The conventional controller tuning is compared with IMC techniques in this work and
it was found that the Ziegler –Nichols controller provides the best control for the
disturbance and the worst for the set-point change, while the IMC controller results
show satisfactory set-point responses but sluggish disturbance responses because the
approximate FOPTD model has relatively small time delay.
Feedforward and feedforward combined with feedback control systems were used as
another strategy to compare with above strategies. Feedforward control provides a
better response to disturbance rejection than feedback control with a steady state
deviation (offset). Thus, a combined feedforward-feedback control system is preferred
in practice where feedforward control is used to reduce the effects of measurable
disturbances, while feedback trim compensates for inaccuracies in the process model,
measurement error, and unmeasured disturbances. Also the deviation (offset) in
feedforward control was eliminated.
Weibull distribution is considered as one of the most widely distribution applied in real life, Its similar to normal distribution in the way of applications, it's also considered as one of the distributions that can applied in many fields such as industrial engineering to represent replaced and manufacturing time ,weather forecasting, and other scientific uses in reliability studies and survival function in medical and communication engineering fields.
In this paper, The scale parameter has been estimated for weibull distribution using Bayesian method based on Jeffery prior information as a first method , then enhanced by improving Jeffery prior information and then used as a se
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The prevention of bankruptcy not only prolongs the economic life of the company and increases its financial performance, but also helps to improve the general economic well-being of the country. Therefore, forecasting the financial shortfall can affect various factors and affect different aspects of the company, including dividends. In this regard, this study examines the prediction of the financial deficit of companies that use the logistic regression method and its impact on the earnings per share of companies listed on the Iraqi Stock Exchange. The time period of the research is from 2015 to 2020, where 33 companies that were accepted in the Iraqi Stock Exchange were selected as a sample, and the res
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Bivariate time series modeling and forecasting have become a promising field of applied studies in recent times. For this purpose, the Linear Autoregressive Moving Average with exogenous variable ARMAX model is the most widely used technique over the past few years in modeling and forecasting this type of data. The most important assumptions of this model are linearity and homogenous for random error variance of the appropriate model. In practice, these two assumptions are often violated, so the Generalized Autoregressive Conditional Heteroscedasticity (ARCH) and (GARCH) with exogenous varia
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