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Much of the fuzzy literature uses set such as, filling or emptying a reactor, heating or theory notation which obscures the ease of the mixing a product. Intelligent control is a control formulation of a fuzzy controller. Although the system with the ultimate degree of autonomy in terms controllers are simple to construct, the proof of of self-learning, self-reconfigurability, reasoning, stability and other validations remain important planning and decision making, and the ability to topics. The outline of fuzzy operations will be shown extract the most valuable information from here through the design of a familiar room unstructured and noisy data from any dynamically thermostat.

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Complex of a fuzzy model which can take one or more fuzzy industrial processes such as a batch chemical values, each represented by a fuzzy set and a word reactors; blast furnaces, cement kilns and basic descriptor. The room temperature is the variable oxygen steel making are difficult to control shown in Fig.

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The of available measurements. In such cases automatic power of a fuzzy model is the overlap between the control is applied to those subsidiary variables, which fuzzy values. A single temperature value at an instant can be measured and controlled, for example in time can be a member of both of the overlapping temperatures, pressures and flows. The overall sets. In conventional set theory, an object in this case process controls objectives, such as the quality and a temperature value is either a member of a set or it quantity of product produced, has been left in the is not a member.

This implies a crisp boundary hands of the human operators in the past [2]. In recent between the sets. In fuzzy logic, the boundaries years, computational intelligence has been used to between sets are blurred. In the overlap region, an solve many complex problems by developing object can be a partial member of each of the intelligent systems. Fuzzy logic has proved to be a overlapping sets. The blurred set boundaries give powerful tool for decision-making systems, such as fuzzy logic its name.

Fuzzy logic and neural networks - Applications to analytical chemistry

By admitting multiple expert and pattern classification systems. Fuzzy set possibilities in the model, the linguistic imprecision theory has been used in some chemical process. In is taken into account. The membership functions traditional rule-based approaches, knowledge is defining the three fuzzy sets shown in Fig. There are no constraints on the structure. When new data are encountered, it is specification of the form of the membership matched to the antecedent's clause of each rule, and distribution. The Gaussian form from statistics has those rules where antecedents match a data exactly been used, but the triangular form is commonly are fired, establishing the consequent clauses.

This chosen as its computation is simple.

The Fuzziness of the Molecular World and Its Perspectives

The number of process continues until the desired conclusion is values and the range of actual values covered by each reached, or no new rule can be fired. In the past one is also arbitrary. Finer resolution is possible with decade, fuzzy logic has proved to be useful for additional sets, but the computation cost increases.

In this research, we investigate these steps. The first is fuzzification, where measurements applications in more detail. The 4. Piping risk assessment second step is the application of the linguistic model, Pipelines are generally recognized to be the safest usually in the form of IF—THEN rules. Finally the and most economical way of transporting hazardous resulting fuzzy output is converted back into physical substances in comparison with other methods of values through a defuzzfication process. However, the 3. Since Fuzzy to the environment and substantial losses.

Adam et al. Logic Control FLC does not require a model and explore the application of the fuzzy logic for risk the control is based on expertise human reasoning, assessment of major hazards connected with they have been applied in many control schemes. Every pipelines [5]. Safety analysis inference engine and defuzzifier Figure 2. The Process and chemical plants, where large amounts of advantages of fuzzy controllers based on fuzzy logic dangerous chemical substances are stored and systems are intuitive design, reflecting the behavior handled, may be subjected to different types of of human operator, the fact that the model of the hazards including natural hazards, process hazards as controlled process is not necessary an important well as terrorist and criminal acts.

A successful feature when ill-defined processes are to be management of such facilities requires pertinent controlled , and good control quality not worse than information and good judgment about the hazards that of classical controllers. However, the main posed by the activity of that facility.

Process Safety Analysis PSA , being a basis for decision-making process in chemical industry is a very complex task, representing a number of uncertainties connected with information shortages which may lead to the important overlooking of the safety assurance of plants.

Medicinal Chemistry and Fuzzy Logic

The application of fuzzy sets may improve data acquisition process. Efforts to provide work safety in workplaces, such as risk management, are not only important for the health of workers but also inevitable managerial activities for economic and financial performance, productivity of the facility and the quality and continuity of production [7]. Because of the hazardous nature of construction work, occupational safety is a serious problem in the Figure 2: Fuzzy Logic System construction industry.

The nature of construction 4.

Additionally recognition. Gurcanli and Mungen proposed a technique, would be effectively used for improved method for assessment of the risks that workers process control of FCC in refinery process industry expose to at construction sites using a fuzzy rule- [11]. Classification of product qualitative insufficient data. Using this approach, historical There are many chemical engineering processes, accident data, subjective judgments of experts and where the quality characteristics of the product the current safety level of a construction site can be cannot be measured objectively either on-line due to combined.

In the scope of this study, first the lack of proper sensors or off-line due to the occupational accidents in the construction industry absence of any measuring devices. In these cases, a are identified from 40, unclassified occupational human expert is employed to assign the product accidents in all industries [8].

Pure and Applied Chemistry

The method is then quality characteristics to certain predefined categories implemented on a tunneling construction site and risk classes , based on his experience and perceptions. Furnace control perform the classification usually requires the Many furnaces have very long time constants and no interruption of the process in order to collect a single variable that can be used to control the sample. Furthermore, this way of classifying the process. For these furnaces rule-based expert systems product quality is very subjective and may lead to and fuzzy logic control systems are commonly used.

The control system then adjusts the other accurately measured process variables. These systems effectively mimic the to perform quality classifications. The methodology best human operators but do so with greater performs remarkably well in two different cases, consistency than real operators are able to maintain.

Separation Process and tune. However, the increased production, In chemistry and chemical engineering, a separation improved product quality and reduced specific process is used to transform a mixture of substances energy consumption ensures that the return on into two or more distinct products. The separated investment is very good [9]. Modeling of the Fluidized Catalytic Cracking physical property, such as size, or crystal Unit of a Petrochemical Refinery modification or other separation into different Fluid catalytic cracking FCC is an important oil components.

Optimization gas streams is of great importance economically. FCC processes are known to be very separation process with rubbery membranes such as difficult to model and control because of the large poly dimethyl siloxane PDMS becomes rational. Osofisan and Obafaiye describe different membranes. The developed model is able to investigations carried out regarding the application of choose the best conditions of preparation for the next Fuzzy Logic Control to the Fluidized Catalytic membranes heuristically.

This research has demonstrated and 4. Also, Taskin et al.

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They indicated how Figure 3. Reactor control In chemical engineering, chemical reactors are vessels designed to contain chemical reactions. Chemical engineers design reactors to maximize net present value for the given reaction. Bioreactor Penicillin G acylase PGA is an important enzyme used as biocatalyst in the production of semisynthetic b-lactam antibiotics. Many microorganisms produce this enzyme and recombinant Escherichia coli has been preferred use for industrial applications.

Bacillus megaterium is one of the microorganisms that excrete this enzyme into the medium. As a Figure 3 A schematic flow diagram of oil consequence, separation and purification steps are 4. Food Produce simplified. On-line measurement of enzyme activity Automation of industrial oven production lines used during cultivation using in-situ sensors is a difficult for cooking biscuits interests biscuit manufacturers task in the industrial environment due to the lack of both in France and Germany. Figures and Tables. Citations Publications citing this paper. Toropova , Andrey A. Genetic fuzzy learning Marco Russo.

References Publications referenced by this paper. Correlation of biological activity of phenoxyacctic acids with hammett substituent and partition coelficients. Hansch , P. Malone , T. Fujita , R. A genetic approach to fuzzy learning.

Neural Networks for Pattern Recognition. HIV - I reverse transcriptase inibitor design using artilicial neural networks. Tecto , V.