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Baiesu A.-S.,Petroleum Gas University of Ploiesti
Control Engineering and Applied Informatics | Year: 2011

Because the process dynamics tend to become too complex to be efficiently controlled, there is always a need to develop innovative control technologies, in order to obtain high economic performance. A way to achieve this objective is to use one of the control strategies which rely on the controlled process model such adaptive control, model predictive control, internal model control, robust control. In order to use one of these control techniques, the process model has to be obtained. The purpose of this paper is to present a model identification method, based on Markov parameters, for a nonlinear chemical process, the propylene/propane binary distillation column.

Toader F.A.,Petroleum Gas University of Ploiesti
Studies in Informatics and Control | Year: 2015

The Job Shop Scheduling Problem (JSSP) is regarded as one of the most challenging issues by the research community in this field due to its complexity. This paper presents a hybrid algorithm called H-PSO-SA for JSSP which is a mixture of two computational artificial intelligence algorithms: Particle Swarm Optimization and Simulated Annealing. In order to demonstrate efficiency of the proposed hybrid algorithm, a series of tests are conducted using a set of classical JSSP benchmarks. The schedule results are compared with outcomes well known in the scientific literature. © ICI Bucharest 2010-2015.

Manea M.,Petroleum Gas University of Ploiesti
Revue Roumaine de Chimie | Year: 2012

Drilling fluids, dispersed systems that have to meet specific technological requirements in order to be used in the process of oil wells drilling have been recently intensly studied. The major aim of the research is to increase the technological efficiency of these systems, to make them environmentally friendly and economical. The paper presents the designing of novel drilling fluids together by applying nanotechnology to wells drilling technology. The author focused on low solid content water-based drilling fluids prepared with polymers. Two polymers were tested to adjust specific properties and their performance was studied comparatively for particles sizes in micro and nano scale. Treatments of alkalisation and density increase were performed on an initial system, evaluating the response to them by measurements on the entire set of standard properties.

In the second part of the paper is presented the hierarchical control structure, which is organized on three levels: conventional control level, advanced control level, and optimal control level; each levels being characterized by the output - input values and by dynamic characteristics. The author gives special attention to the second level, where was developed based on a model predictive controller. The investigation of performances for the predictive controller was performed using the dynamic simulator presented in the first part of the paper. From economic point of view, the development and the implementation of the hierarchical control structure for the catalytic cracking process is leading to increase the overall plant efficiency.

Oprea M.,Petroleum Gas University of Ploiesti
International Journal of Artificial Intelligence | Year: 2012

Artificial intelligence provides a variety of techniques and methods that can be implemented in the environmental decision support systems, for solving different problems such as forecasting, analysis, diagnosis, control and planning, for a better quality of the environment and, thus, of the life. The paper presents an intelligent system, INTELLEnvQ-Air that was developed for air quality analysis in urban regions and for informing the population about the impact of air pollution on human health and possible measures of protection for vulnerable persons. The system integrates two artificial intelligence approaches: feed forward artificial neural networks, for air pollutants concentrations forecasting, and rule-based expert systems for the analysis of air quality and human health impact. © 2012 by IJAI (CESER Publications).

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