Direct digital control of a micro-machine model power system
This thesis describes the theory, construction and development of a direct digital control scheme for a micro-machine model of an electrical power generating system. The areas of research covered by this thesis fall into four main regions: 1. The design and development of digital transducers to redu...
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University of Bath
1977
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Online Access: | https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.450312 |
Summary: | This thesis describes the theory, construction and development of a direct digital control scheme for a micro-machine model of an electrical power generating system. The areas of research covered by this thesis fall into four main regions: 1. The design and development of digital transducers to reduce the noise and accuracy problems associated with analogue techniques. 2. The design and development of a fast and flexible real-time interface between the supervisory computer and the controlled system based on the use of dedicated microprocessors. 3. The development of a software real-time operating system and program suite to allow rapid implementation of a required control philosophy for the laboratory system. 4. The practical implementation of sub-optimal excitation control of the synchronous generator by state feedback techniques. The digital control scheme described has been designed as a flexible base for future work in the implementation of full excitation and governor control of the micromachine system. It is modular in concept to allow rapid application of various forms of modern control philosophy to the laboratory model system. Various support facilities of wider application have also been developed including a microprocessor to computer interface, a direct-loading cross-assembler and an on-line microprocessor debugging system. The excitation control implemented in this study involves the addition of state feedback signals to a fast-acting voltage regulator to improve the transient stability limit. The coefficients of the feedback matrix are determined by an offline parameter optimisation technique to minimise a quadratic performance index of the non-linear system model. This control is shown to effect significant improvements in the system response following the occurrence of a severe disturbance to the system. |
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