This investigation sought to explore the relationship of Julian Rotter's concept of internal versus external control (I-E) to stages of moral judgment. The I-E dimension is defined as the attribution by the individual of responsibility for behavioral outcomes to either oneself or to outside entities. The internal oriented person believes that the events in which he is involved lie within his control. Conversely, the external oriented person believes that the events that happen to him are controlled by other factors.

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This work reports the developnent of a mathenatical model and distributed, multi variable computer-control for a pilot plant double-effect climbing-film evaporator. A distributed-parameter model of the plant has been developed and the time-domain model transformed into the Laplace domain. The model has been further transformed into an integral domain confooning to an algebraic ring of polynomials, to eliminate the transcendental terms which arise in the Laplace domain due to the distributed nature of the plant model. This has made possible the application of linear control theories to a set of linear-partial differential equations • . The models obtained have well tracked the experimental results of the plant. A distributed-computer network has been interfaced with the plant to implement digital controllers in a hierarchical structure. . A modern rnultivariable Wiener-Hopf controller has been applled to the plant model. The application has revealed a limitation condition that the plant matrix should .be positive-definite along the infinite frequency axis. A new multi variable control theory has emerged fram this study, which avoids the above limitation. The controller has the structure of the modern Wiener-Hopf controller, but with a unique feature enabling a designer to specify the closed-loop poles in advance and to shape the sensitivity matrix as required. In this way, the method treats directly the interaction problems found in the chemical processes with good tracking and regulation perfo~noes. Though the ability of the analytical design methods to determine once and for all whether a given set of specifications can be met is one of its chief advantages over the conventional trial-and-error design procedures. However, one disadvantage that offsets to some degree the eno~us advantages is the relatively complicated algebra that must be employed in working out all but the simplest problem • . Mathematical algorithms and computer software have been developed to treat some of the mathematical operations defined over the integral domain, such as matrix fraction description, spectral factorization, the Bezout identity, and the general manipulation of polynomial matrices. Hence, the design problems of Wiener-Hopf type of controllers and other similar algebraic design methods can be easily solved.

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Modelling and control of non-linear systems are not easy, which are now being solved by the application of neural networks. Neural networks have been proved to solve these problems as they are described by adjustable parameters which are readily adaptable online. Many types of neural networks have been used and the most common one is the backpropagation algorithm. The algorithm has some disadvantages, such as slow convergence and construction complexity. An alternative neural networks to overcome the limitations associated with the backpropagation algorithm is the Radial Basis Function Network which has been widely used for solving many complex problems. The Radial Basis Function Network is considered in this theses, along with a new adaptive algorithm which has been developed to overcome the problem of the optimum parameter selection. Use of the new algorithm reduces the trial and error of selecting the minimum required number of centres and guarantees the optimum values of the centres, the widths between the centres and the network weights. Computer simulation usmg SimulinklMatlab packages, demonstrated the results of modelling and control of non-linear systems. Moreover, the algorithm is used for selecting the optimum parameters of a non-linear real system 'Brushless DC Motor'. In the laboratory implementation satisfactory results have been achieved, which show that the Radial Basis Function may be used for modelling and on-line control of such real non-linear systems.

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Call number: LD2668 .T4 1958 G74 / Master of Science

M.Ing. / This research project is dedicated to the automation of environmental control within greenhouses. To create an optimal climate in the greenhouse, the main environmental parameters that need to be controlled are temperature, humidity and light intensity. As a result of process dead times and the extreme interdependence of these parameters, the control problem can be classified as non-linear and multi-variable. In the past, most greenhouse environmental control systems depended on the decision making of an experienced human operator. This often gave rise to trial and error, especially when new species were established. With the current advances in "intelligent" control systems and high accuracy sensors, more and more of the decisions involved in greenhouse control can be automated. In this way more emphasis can be placed on emulating the abilities of an expert operator, by means of a computerbased automatic control system. In this research project, "intelligent" as well as "non-intelligent" control techniques, for addressing the problem of automated climate control in a greenhouse, are investigated. These include PID-control as a "non-intelligent" technique, and rule-based fuzzy logic control and self-learning fuzzy logic control as two "intelligent" control techniques. These techniques are all applied to experimental greenhouse which is equipped with management mechanisms, such as fans, heaters, sprinklers and lights. The results of the experiments are evaluated according to two performance parameters: the Control Performance Index (CPI) and the Mean Square Error (MSE). The three techniques are not only assessed for their efficiency, but also for their applicability to the greenhouse environmental problem. Each of the control techniques has a unique characteristic response to the non-linear, non-stationary, multi-variable problem of environmental control and are subsequently addressed in the respective chapter.

Tesis para optar al grado de Magíster en Control de Gestión / El objetivo general de este trabajo es la aplicación de un sistema de control a un proyecto del área ingenieril basado en la ingeniería del EV.