Values Of Control Variables Research Articles

Individual controlled junctions: Optimal design

The phase-based approach is a recent evolution in the field of undersaturated isolated junction control optimization. Using the incompatibilities among the streams, it proceedes calculating the control variable values without the external individuation of a stage matrix. One of these methods, based on a binary linear mathematical model, performs the simultaneous optimization of cycle time, green splits and green scheduling. The model, however, requires a preliminary decision about the composition of the streams and their assignment to the lanes. The flow ratios of the streams, indeed, have to be supposed constant during the cycle. In this paper an idea to remove this last hypothesis is described. It is based on a simple model regarding the behaviour of the users belonging to streams coming from the same access. A numerical example using a test junction is shown; the obtained results are compared to the ones deriving from a standard phase-based method.

Direct digital control, auto-tuning and supervision using fuzzy logic

We describe algorithms for the design and implementation of fuzzy logic controllers and present results of their application to temperature control of a heated air-stream. Auto-tuning methods are studied for adjustment of conventional parameters to compensate for actual values of control variables, or of external variables; and for improvement of performance from observation of results. Conditions for verifying the consistency of the linguistic protocol with its implementation are presented in an appendix.

On Line Steady State Security Assessment and Enhancement of an Energy System Using Pattern Recognition Techniques

Pattern recognition technique (PRT) are now accepted tools for handling situations demanding dimensionality reduction, proper identification of states of system and for arriving at a reliable decision. On line control functions fall in domain of such situations. This report gives a systematic approach to cater to such problems using PRT. A three class, linear classifier is designed. Further, an interactive classifier is described using principal component method, and is compared with other available techniquesTwo separate classifiers are reported for peak and off-peak loading conditions using repetative projection technique. Classifiers are tested on sample system and results are reported. If the decision is mapped into area which confirm need for a corrective control action, the security enhancement algorithm is activated. Revised values of control variables are obtained using gradient projection matrix

A prototype DSS for structuring and diagnosing managerial problems

A methodology for managerial problem recognition, structuring, and diagnosis is presented. The system integrates diagnostic concepts from artificial intelligence with database management and structural modeling techniques. Given an organizational database, a user specifies control bounds for selected data items and causal relationships between variables in the database. Structural modeling techniques are used to represent knowledge of causal relations. If a control variable's value is out of bounds, structural models are used in an attempt to diagnose (explain) the discrepancy. If the discrepancy is explained, a diagnosis is at hand. If not, the user's model is somewhat deficient and what-if analysis can be used to construct an improved model. This methodology has been implemented in a prototype decision support system (DSS) that is described, along with an example of its use.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Signature Analysis for Mechanical Systems via Dynamic Data System (DDS) Monitoring Technique

A new modeling technique called Dynamic Data System (DDS) is introduced for signature analysis. A one-horsepower electric motor experiment is used to demonstrate the methodology. The ‘normal’ operation is simulated by idling runs and eccentric loads representing the ‘defective’ operations. A DDS Monitoring Technique, by employing statistical quality control theory, is developed to monitor the operations of imposed electric motor defects. It takes thirteen seconds for data processing and calculation of a control variable value from an On-line programmed microprocessor to provide the control justification. The DDS Monitoring Technique proves to be effective and sensitive in identifying the operational status of a mechanical system.

Consideration of Random Factors in Optimal Scheduling of Power Systems

The problem of optimal scheduling of power systems under the risk taking situations is discussed. At that there are taken into account the probabilistic information about initial data and deviations of factual values of controllable variables from their optimal planned values. The method of planned characteristics (functions) is proposed and some results of use of that method for optimization of load distributions in thermal power plants and hydro-thermal power systems are considered.

An Economically Optimum Aquaculture Facility1

ABSTRACTA method for determination of optima 1 values of control variables in an aquaculture facility has been presented previously (Botsford et al., 1974a). This paper describes major improvements in the optimization approach and use of the approach in design and evaluation of culture systems. Added features of the optimization approach include determination of optimum market size, discrete rather than continuous space allotment, and a new waste treatment model. In addition, recent experimental results and proposed physical system designs have been incorporated in the model enabling more accurate optimization and more realistic predictions. The influence of geographic location, changes in cost of various components, and effects of experimental uncertainty of biological parameters on optimal values of control variables and final costs are described. The numerical results presented are for the American lobster (Homarus americanus); however, the techniques of analysis used may be applied to culture of other species.

APPLICATION OF OPTIMIZATION THEORY TO THE ECONOMICS OF AQUACULTURE4

ABSTRACTEngineering methods of system analysis and optimal control theory are applied to the commercial raising of aquatic species. Mathematical models of aquaculture system components are discussed and optimization theory is applied to the design and operation of an aquaculture facility. The models are formulated in terms of variables which describe the condition of the system (State Variables) and variables which influence the condition of the system (Control Variables). The State Variables are the number of animals in a batch, their average weight, and their cost. The Control Variables relate to the water temperature, water recirculation or replacement, space per animal, amount of food per animal, and kind of food. Differential equation which relate the State Variables to the Control Variables are presented. Mathematical optimization techniques are used to determine the values of Control Variables which minimize the cost. The use of the Technique in research and design of an aquaculture facility is discussed and sample numerical results are presented for lobster culture.

The Effect of the Demand Distribution in Inventory Models Combining Holding, Stockout and Re-Order Costs

Summary The well-known square-root formula of inventory theory is based on the assumption of known, constant demand. When demand is probabilistic, the values of inventory control variables which minimize the expected total costs will depend on the shape of the distribution. In this paper we consider the effect of several demand distributions on a re-order cycle inventory system; however, the method of analysis is standard and could be applied to a number of other models. Formulae for the iterative calculation of optimal values of control variables are derived, and illustrated by worked examples. In the process, some results in distribution theory are developed.