Author(s):
Mirzaeian ، Moalle & Lucas


Abstract:
In this paper a fuzzy expert system for predicting the performance of a switched reluctance motor has been developed. The design vector consists of design parameters, and output performance variables are efficiency and torque ripple. An accurate analysis program based on Improved Magnetic Equivalent Circuit (IMEC) method has been used to generate the input-output data. These input-output data is used to produce the initial fuzzy rules for predicting the performance of Switched Reluctance Motor (SRM). The initial set of fuzzy rules with triangular membership functions has been devised using a table look-up scheme. The initial fuzzy rules have been optimized to a set of fuzzy rules with Gaussian membership functions using gradient descent training scheme. The performance prediction results for a 6/8, 4kw, SR motor shows good agreement with the results obtained from IMEC method or Finite Element (FE) analysis. The developed fuzzy expert system can be used for fast prediction of motor performance in the optimal design process or on-line control schemes of SR motor.

Keywords:
Fuzzy Expert System, SR Motor, Performance Prediction

Author(s):
M. Golabchi


Abstract:
Expert system technology provides a new opportunity for organising and systematising the
available knowledge and experience in the structural selection domain. Computerisation, in
general, and expert system technology, in particular, can provide assistance for the engineers by giving much greater access to information, knowledge and expertise and by processing this information. This paper presents an interactive expert system called Structural Selection Expert System (SSE) that assists engineers and designers in the choice of the most appropriate structural system for a particular function to meet proposed criteria. It can be used as a teaching aid for architecture, civil engineering and structural design students. The paper explains why the selection of suitable structures for a particular function was considered appropriate for an expert system, then the knowledge acquisition techniques are described. The different tools used to develop expert systems are briefly discussed with emphasis on the implementation methodology and tools adopted in the research. The advantages of implementing the SSE using object-oriented development and Kappa-PC are presented. Knowledge representation in the SSE and the techniques adopted to represent the structural systems knowledge is discussed. The inference mechanism in the SSE is described in some detail, followed by hardware requirements for the system.

Keywords:
Expert system; knowledge، based; structural systems; large spans; forward and backward chaining; appropriate solution