A general system for controlling an unknown process by adjusting compensation networks is discussed. The control operation is divided into two parts, that of identification of the unknown process dynamics and that of adaption by adjusting the compensation networks. Both operations are carried out by the method of steepest descent, using a suitable error signal as a performance function. A general method of investigation is considered, which is applicable to all systems of this type. The systems are classified as Type I and Type II; it is shown that a Type I system is stable for all input signals and initial conditions. The systems which are not of Type I are designated as Type II and it is shown that the behaviour of Type II systems can be approximated by that of a Type I system in the neighbourhood of the optimum point of operation. These results are applied to investigating the behaviour of a number of controllers and identification systems. / Applied Science, Faculty of / Electrical and Computer Engineering, Department of / Graduate

This thesis deals with the identification of parameters in distributed parameter systems. Two sensitivity methods, namely; Meissinger's method and the method of structural sensitivity are extended to obtain the sensitivity coefficients of discretized distributed parameter systems. The method of Bingulac and Kokotovic is extended to identify parameters in the one and the two dimensional parabolic differential equations. CSMP (continuous system modeling programme) is used throughout to simulate the systems. Results for both sensitivity schemes are obtained, and it is found that although structural sensitivity is advantageous for parameter identification in ordinary differential equations, this is not the case for partial differential equations. / Applied Science, Faculty of / Electrical and Computer Engineering, Department of / Graduate

LD2668 .T4 1966 D3 / Master of Science

published_or_final_version / Electrical Engineering / Master / Master of Science in Engineering

published_or_final_version / Physics / Master / Master of Philosophy

published_or_final_version / Physics / Master / Master of Philosophy

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A method is developed to estimate the projection of a higher dimensional (three or more) controllable set onto a lower dimensional (usually one or two) space. This method requires that an n-dimensional dynamical system subject to a scalar control be transformed into two lower dimensional subsystems by choosing a proper transformation matrix. It is shown that such a transformation can always be determined for an n-dimensional linear I/O system. For some nonlinear dynamical system problems such as an aircraft missile avoidance problem, a proper transformation matrix still can be determined. From the transformed system, both an overestimate and an underestimate for an actual projected controllable set in the state space of interest can be provided by using the method presented in this dissertation. With these information, the actual projected controllable set can be estimated. Two linear I/O systems subject to a scalar control and an aircraft missile avoidance problem are used to illustrate the method.

No description available.

No description available.