Date of Award
Doctor of Philosophy (PhD)
Electrical and Computer Engineering
Professor N.K. Sinha
There are many different approaches to knowledge based control, in this thesis, three different approaches have been taken for study. These are: -Expert control -Fuzzy logic based control -Qualitative reasoning for control and diagnosis In the first approach, the knowledge based systems acts as a supervisor ro a traditional controller, with the ability to advise an operator about degradation in the performance or if needed tune/change the control algorithm used. This approach is most appropriate when the mathematical model of the systemis known. Several new theoretical insights to the problem of expert control is given in this thesis. An implementation architecture, along with the lessons learned from using such architecture are also discussed.
Alternatively, the knowledge based system may be placed in the control loop; i.e. the control laws may be embedded in rules that are a part of the knowledge based system. Fuzzy logic controllers fall within this category. Fuzzy logic controllers circumvent the problem of designing a controller based on a detail dynamic model by employing the approach of a human operator to an ill-defined system. A step by step procedure for developing such controllers is given in this thesis. This procedure is applied to solve two problems of increasing complexity in the areas of robotic deburring and mobile robotics. Implementation and test results are also given.
The first two knowledge based control techniques have some disadvantages. This is mainly due to the manner in which knowledge is represented, each fact or rule stands on its own as an underivable 'axiom' making it impossible to question the validity or basis of it. Qualitative control system, instead is based on deep knowledge extracted from the understanding of physical interaction between the different components of the plant. This knowledge is used to construct a qualitative model that is used in control operations. In this thesis, an architecture for qualitative control is given and tested on a simple system via simulations. Furthermore, a strategy for expanding qualitative control to provide process diagnostics is also proposed.
Lingarkar, Ravi, "Knowledge Based Control Systems" (1992). Open Access Dissertations and Theses. Paper 1897.