Journal Article•
Optimization method of fuzzy logic controller and its application in compensation of sensors
TL;DR: Compared to other compensation techniques, it is a new,efficient compensation method that not only increases the compensation precision but also maintains the fast calculation ability of the zero-orde T-S fuzzy logic controller.
Abstract: An error collection method for a kind of pressure sensor based on zero-order T-S fuzzy logic controller is presented.Simulated annealing algorithm is used to optimize the parameters of the fuzzy rules.After the temperature compensation,the error is corrected within ±0.3 %,and the temperature coefficients are reduced greatly.Compared to other compensation techniques,it is a new,efficient compensation method that not only increases the compensation precision but also maintains the fast calculation ability of the zero-orde T-S fuzzy logic controller.
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14 Aug 2009
TL;DR: The results of simulation have clearly demonstrated that the proposed fuzzy compensation scheme is better than the non-fuzzy method for detecting automotive exhaust gas.
Abstract: This paper proposes a method of detecting automotive exhaust gas based on fuzzy logic inference after analyzing the principle of the infrared automobile exhaust gas analyzer and the influence of the environmental temperature on analyzer. This paper analyses the measurement error caused by environmental temperature, and then makes a non-linear error correction of temperature for the infrared sensor using fuzzy inference. The results of simulation have clearly demonstrated that the proposed fuzzy compensation scheme is better than the non-fuzzy method.
3 citations
Cites background or methods from "Optimization method of fuzzy logic ..."
...The correction model [10] is shown in Fig....
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...Some compensation measurement should be considered because errors are too high to meet the demand of the measurement precision [6-8, 10]....
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14 Aug 2009
TL;DR: The results of simulation have clearly demonstrated that the proposed fuzzy compensation scheme is better than the non-fuzzy method for detecting automotive exhaust gas.
Abstract: This paper proposes a method of detecting automotive exhaust gas based on fuzzy logic inference after analyzing the principle of the infrared automobile exhaust gas analyzer and the influence of the environmental temperature on analyzer. This paper analyses the measurement error caused by environmental temperature, and then makes a non-linear error correction of temperature for the infrared sensor using fuzzy inference. The results of simulation have clearly demonstrated that the proposed fuzzy compensation scheme is better than the non-fuzzy method.
3 citations