This dissertation introduces, for the first time, the application of Fuzzy Logic Systems (FLS) to the tuning and design of microwave filters. Fuzzy logic deals with artificial intelligence (AI), and can bring human intelligence into problems in a systematic way. Several different algorithms are proposed based on Fuzzy Logic for tuning and design of microwave circuits. The methods take advantage of the ability of Fuzzy Logic systems to incorporate numerical information and linguistic (expert) information, as well as the ability of Fuzzy Logic systems to act as function approximators.;A method to show the ability of capturing human expertise in the form of fuzzy logic controllers is proposed and applied in tuning of 4-pole Chebyshev filters. Moreover, a unique method for microwave filter tuning based on linguistic rules extracted from an expert is developed. The method employs two types of fuzzy controllers, one based on phase response for coarse tuning and the other based on the magnitude response for fine-tuning. This method is shown experimentally for tuning 7-pole and 3-pole Chebyshev iris-coupled waveguide filters by designing a totally automated hardware/software interface. The interface includes high resolution smart motors, custom designed flexible couplings to transfer the motion from the motor shafts to the tuning screws, flexible mounting plates to mount and position the motors, and programming for communication between VNA, PC and motors using GPIB card and serial port.;The theoretical and experimental results given in this thesis verify the validity of the proposed concepts. The thesis has been a pioneer in applying Fuzzy Logic techniques to the tuning and design of microwave circuits.;One of the most interesting applications of FLS is extracting human expert knowledge in the process of post-production tuning of microwave filters, and thus making an automated filter tuning system based on expert rules. Tuning of complex microwave structures have been always a challenge in the microwave engineering area. Fuzzy Logic Systems (FLS) and controllers are found as great means to circumvent this challenge. Promising results for tuning 4-pole chebyshev and 8-pole elliptic filters are obtained for both slightly detuned and highly detuned cases. More robust fuzzy systems based on numerical data are developed using Sugeno type fuzzy logic systems and subtractive clustering to work for both cases of slightly detuned and highly detuned filters at the same time. The FLS techniques are also successfully applied to the design of microwave circuits including couplers, 3-pole and 6-pole filters. The approach could be considered a fast and efficient synthesis method.
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