Title : 
Qualitative reasoning about control
         
        
        
            Author_Institution : 
Fac. of Electr. Eng. & Comput. Sci., Ljubljana Univ. & J. Stefan Inst., Slovenia
         
        
        
        
        
        
            Abstract : 
Qualitative models are better suited for some tasks than the traditional quantitative, or numerical models. These tasks include diagnosis, generating explanation of the system´s behavior and designing novel devices from first principles. It is shown by an example how a qualitative modeling approach can be applied to the control of a dynamic system. The example used is the balancing of a pole on a cart. A control rule is derived from a qualitative model of the pole-and-cart system. This rule is shown to be a straightforward qualitative abstraction of the “classical” control rule derived from the differential equations model of this system
         
        
            Keywords : 
common-sense reasoning; control engineering; control engineering computing; differential equations; explanation; control engineering; control rule; diagnosis; differential equations model; dynamic system; explanation; numerical models; pole balancing; pole-and-cart system; qualitative modeling approach; qualitative reasoning; quantitative models; Artificial intelligence; Control engineering; Control system synthesis; Control systems; Differential equations; Mars; Neural networks; Numerical models; Physics; Robustness;
         
        
        
        
            Conference_Titel : 
Emerging Technologies and Factory Automation, 1993. Design and Operations of Intelligent Factories. Workshop Proceedings., IEEE 2nd International Workshop on
         
        
            Conference_Location : 
Palm Cove-Cairns, Qld.
         
        
            Print_ISBN : 
0-7803-0985-5
         
        
        
            DOI : 
10.1109/ETFA.1993.396424