Title :
A novel fuzzy inferencing methodology for simulated car racing
Author :
Ho, Duc Thang ; Garibaldi, Jonathan M.
Abstract :
This paper describes and further extends the fuzzy inferencing system which won the simulated car racing competition that was arranged as part of FuzzlEEE 2007 conference. The details of the winning non-stationary fuzzy controller and its results are presented. A novel approach to further improve the performance of the winning controller is described and formalised. We term the new fuzzy inferencing method a dasiacontext-dependent fuzzy inference systempsila. The concept of a dasiacontext-dependent fuzzy setpsila that is utilised by the fuzzy system is introduced. Finally, a comparison between context-dependent fuzzy inference system and various existing techniques are carried out on the simulated car racing application. The results show a better performance for context-dependent fuzzy inference systems in stochastic circumstances.
Keywords :
automobiles; digital simulation; fuzzy control; fuzzy reasoning; fuzzy set theory; stochastic processes; FuzzlEEE 2007 conference; context-dependent fuzzy inference system; context-dependent fuzzy set; nonstationary fuzzy controller; simulated car racing; stochastic circumstances; Context modeling; Control systems; Fuzzy control; Fuzzy reasoning; Fuzzy sets; Fuzzy systems; Input variables; Stochastic resonance; Stochastic systems; Uncertainty; Context-dependent Fuzzy Inference System (CDFIS); Context-dependent Fuzzy Sets (CDFS); Fuzzy Inference System (FIS); Non-stationary Fuzzy Inference System (NSFIS); Non-stationary Fuzzy Sets (NSFS);
Conference_Titel :
Fuzzy Systems, 2008. FUZZ-IEEE 2008. (IEEE World Congress on Computational Intelligence). IEEE International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-1818-3
Electronic_ISBN :
1098-7584
DOI :
10.1109/FUZZY.2008.4630630