Abstract
Fuzzy logic controllers are successfully applied in many complex industrial process control tasks due to their special features that other controllers lack or do not have. However, in order to cope with uncertainty in process dynamics or control environments, choosing and optimising a fuzzy controller’s parameters that significantly affect the properties of the control system are indeed a time-consuming. empirical exercise. In this paper, a simplified reasoning method is employed to tune the scaling factors, which is aimed at increasing the speed of fuzzy inference, and simplifying the computing of the complexity and high dimension matrices, so that it can be executed in real time within continuous domains, as well as easily and simply for on-line tuning.
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References
Braae, M., Rutherford, D.A.: Selection of parameters for a fuzzy logic controller. Fuzzy Sets and Systems, 2185–2199 (1979)
Chou, C.-H., Lu, H.-C.: A heuristic self-tuning fuzzy controller. Fuzzy Sets and System 61, 249–264 (1994)
Driankov, D., Hellendoorn, H., Reinfrank, M.: An Introduction to Fuzzy Control. Springer, Heidelberg (1996)
Eihajjaji, A., Rachid, A.: Analytic formulation of linguistic rules for fuzzy controllers. Fuzzy Sets and Systems 73, 219–225 (1995)
Filev, D.P., Yager, R.R.: On the analysis of fuzzy logic controllers. Fuzzy Sets and Systems 68, 39–66 (1994)
Ichihashi, Tanaka, H.: PID-fuzzy hybrid controller. In: Proc. 4th Fuzzy Systems Symp., pp. 97–102 (1988)
Ju, M.S., Yang, D.L.: Design of adaptive fuzzy controls based on natural control lows. Fuzzy Sets and Systems 81, 191–204 (1996)
Lu, S.-R.: Production method of fuzzy controller parameters adjustment. Basic Automation (Chinese) 4, 4–6 (1999)
Mizumoto, M.: Fuzzy controls under various fuzzy reasoning methods. Information Science 45, 129–151 (1988)
Mizumoto, M.: Realization of PID controls by fuzzy control methods. Fuzzy Sets and Systems 70, 171–182 (1995)
Mizumoto, M.: Product-sum-gravity method = fuzzy singleton-type reasoning method = simplified reasoning method. In: Proc. 5th IEEE Int. Conference on Fuzzy Systems, pp. 2098–2102 (1996)
Qiao, W.Z., Mizumoto, M.: PID type fuzzy controller and parameters adaptive method. Fuzzy Sets and Systems 78, 23–35 (1996)
Sun, G.-S., Lan, X.-Z.: Engineering fuzzy control. Machinery Industrial Press, Beijing (1995) (in Chinese)
Sun, Q.-Z.: Theory and technology for intelligent control. Qinghua University Press, Beijing (1997) (in Chinese)
Woo, Z.-W., Chung, H.-Y., Lin, J.-J.: A PID type fuzzy controller with self-tuning scaling factors. Fuzzy Sets and Systems 115, 321–326 (2000)
Verbruggen, H.B., Bruijn, P.M.: Fuzzy control and conventional control: What is (and can be) the real contribution of fuzzy systems? Fuzzy Sets and Systems 90, 151–160 (1997)
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Yan, F., Lu, Sr. (2009). On-Line Inference for Fuzzy Controllers in Continuous Domains. In: Cao, B., Li, TF., Zhang, CY. (eds) Fuzzy Information and Engineering Volume 2. Advances in Intelligent and Soft Computing, vol 62. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03664-4_118
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DOI: https://doi.org/10.1007/978-3-642-03664-4_118
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-03663-7
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