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Advantages of adaptive fuzzy logic control for digital excitation systems

Posted on:2001-08-14Degree:Ph.DType:Dissertation
University:New Mexico State UniversityCandidate:Chen, HongFull Text:PDF
GTID:1468390014453657Subject:Engineering
Abstract/Summary:
The purpose of a synchronous-machine excitation system is to control the terminal voltage and reactive power of a synchronous machine for supplying reliable and efficient electric power in the utility industry. Excitation control is also well known as one of the effective means to enhance the overall voltage stability of electric power systems. Conventional excitation control systems have been successfully implemented in actual power systems for many years; however, the parameters, such as gains and time constants, have traditionally been fixed to ensure the system's optimal performance at only one nominal operating point. Consequently, system performance is degraded whenever its operating point is shifted from the nominal point.; Progress in computer technology provides the potential for fast calculation of more sophisticated algorithms in real-time. Embedded software with modern excitation-system hardware can improve the decision-making process in excitation control applications. New control algorithms can be designed to adapt to changing operational conditions of the plant. The purpose of this dissertation is to study and implement several of these algorithms for applications to the excitation control of the synchronous machine, thus overcoming the disadvantages of the widely-used conventional control approaches.; Four types of controllers are examined and implemented for digital excitation control systems (DECS). They are proportional-integral-derivative controller (PIDC), adaptive self-tuning controller (ASTC), fuzzy logic controller (FLC), and adaptive fuzzy logic controller (AFLC). Each of them is modeled, simulated, and programmed. The methods are applicable to both static and rotating excitation systems. Comparative studies of each controller for DECS applications in this research conclude that the AFLC with learning mechanisms and plant-model independent features can automatically tune the fuzzy logic controller so that it can adapt to different plant conditions, such as setpoint regulation, the effect of unknown load disturbances, large parameter variations, and variable dead time in the system. The advantages and disadvantages of each control approach as applied to a DECS are also summarized.
Keywords/Search Tags:Excitation, System, Fuzzy logic, DECS, Adaptive, Power
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