Abstract:
This paper presents an alternative method to design a fuzzy neural network (FNN) using a set of nonoverlapped block pulse membership functions (BMPFs), and this FNN with ...Show MoreMetadata
Abstract:
This paper presents an alternative method to design a fuzzy neural network (FNN) using a set of nonoverlapped block pulse membership functions (BMPFs), and this FNN with nonoverlapped BPMFs will be shown to be equivalent to the conventional table lookup (TL) technique. Therefore, the hidden links between TL and FNN techniques are revealed in this paper that provides a methodology to design a TL controller based on the FNN design concept. In order to do so, a new direct formula is first developed to generate the fuzzy rules from the premise part in FNN. This direct formula not only guarantees a one-to-one mapping that maps the fuzzy membership functions onto the fuzzy rules, but also alleviates the coding effort during hardware implementation. It is further elaborated that the FNN with nonoverlapped BPMFs has the advantage of faster online training that requires less computation time, but at the cost of more memory requirement to store the fuzzy rules. The application of this new approach has been applied successfully in the water injection control of a turbo-charged automobile with excellent results.
Published in: IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews) ( Volume: 38, Issue: 4, July 2008)
Citations are not available for this document.
Contents Cites in Papers - |
Cites in Papers - IEEE (11)
Select All
1.
Tao Shen, Junyong Zhai, "Reactive Obstacle Avoidance Strategy Based on Fuzzy Neural Network and Arc Trajectory", 2019 Chinese Automation Congress (CAC), pp.4792-4796, 2019.
2.
Jing Wang, Yuan-Yan Tang, Long Chen, C. L. Philip Chen, Chao-Tian Chen, "A new fast-F-CONFIS training of fully-connected neuro-fuzzy inference system", 2015 International Conference on Informative and Cybernetics for Computational Social Systems (ICCSS), pp.99-104, 2015.
3.
Jing Wang, Chao-Tian Chen, C. L. Philip Chen, Yong-Quan Yu, "Mixed radix systems of fully connected neuro-fuzzy inference systems with special properties", 2015 International Conference on Informative and Cybernetics for Computational Social Systems (ICCSS), pp.105-109, 2015.
4.
C. L. Philip Chen, Jing Wang, Chi-Hsu Wang, Long Chen, "A New Learning Algorithm for a Fully Connected Neuro-Fuzzy Inference System", IEEE Transactions on Neural Networks and Learning Systems, vol.25, no.10, pp.1741-1757, 2014.
5.
Jing Wang, Chi-Hsu Wang, C. L. Philip Chen, "The Bounded Capacity of Fuzzy Neural Networks (FNNs) Via a New Fully Connected Neural Fuzzy Inference System (F-CONFIS) With Its Applications", IEEE Transactions on Fuzzy Systems, vol.22, no.6, pp.1373-1386, 2014.
6.
Jing Wang, C. L. Philip Chen, Chi-Hsu Wang, "On the conjugate gradients (CG) training algorithm of fuzzy neural networks (FNNs) via its equivalent fully connected neural networks (FFNNs)", 2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pp.2446-2451, 2012.
7.
Jing Wang, C. L. Philip Chen, Chi-Hsu Wang, "Finding the near optimal learning rates of Fuzzy Neural Networks (FNNs) via its equivalent fully connected neural networks (FFNNs)", 2012 International Conference on System Science and Engineering (ICSSE), pp.137-142, 2012.
8.
Dexin Liu, Xiaoli Li, Shuting Lu, Dawei Ding, Xianzhong Chen, "Application of fuzzy neural network in burden surface clustering", 2012 24th Chinese Control and Decision Conference (CCDC), pp.1094-1099, 2012.
9.
Jing Wang, Chi-Hsu Wang, C. L. Philip Chen, "On the BP training algorithm of Fuzzy Neural Networks (FNNs) via its equivalent fully connected neural networks (FFNNs)", 2011 IEEE International Conference on Systems, Man, and Cybernetics, pp.1376-1381, 2011.
10.
Sau Wai Tung, Chai Quek, Cuntai Guan, "FAPOP: Feature analysis enhanced pseudo outer-product fuzzy rule identification system", 2011 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2011), pp.1530-1537, 2011.
11.
Jose Luis Aznarte, Jose Manuel Benitez, "Equivalences Between Neural-Autoregressive Time Series Models and Fuzzy Systems", IEEE Transactions on Neural Networks, vol.21, no.9, pp.1434-1444, 2010.
Cites in Papers - Other Publishers (7)
1.
Nan Zhang, Rami Bahsoon, Nikos Tziritas, Georgios Theodoropoulos, "Knowledge Equivalence in Digital Twins of Intelligent Systems", ACM Transactions on Modeling and Computer Simulation, 2023.
2.
Chi-Hsu Wang, Kar-Chun Hor, "From fuzzy center average defuzzifier (CAD) to fuzzy lookup table controller (FLTC) with an efficient Heaviside search algorithm (HSA)", Neural Computing and Applications, vol.31, no.9, pp.5135, 2019.
3.
Chi-Hsu Wang, Kar-Chun Hor, Wei-Chuan Chen, "Fuzzy Lookup Table Controller (FLTC) via Center Average De-fuzzifier (CAD) with a New Efficient Heaviside Search Algorithm (HSA) for Lookup Table Implementation", IOP Conference Series: Materials Science and Engineering, vol.428, pp.012050, 2018.
4.
Chi-Hsu Wang, Chun-Yao Chen, "Intelligent Chaos Synchronization of Fractional Order Systems via Mean-Based Slide Mode Controller", International Journal of Fuzzy Systems, vol.17, no.2, pp.144, 2015.
5.
Chi-Hsu Wang, Chih-Cheng Wang, "Finding the Real Surge Boundaries of Turbo-charged Automobiles Using Intelligent Fuzzy Reasoning Technique", International Journal of Fuzzy Systems, vol.17, no.2, pp.224, 2015.
6.
Hansoo Choi, "Tuning Method of the Membership Function for FLC using a Gradient Descent Algorithm", Journal of the Korea Academia-Industrial cooperation Society, vol.15, no.12, pp.7277, 2014.
7.
Gang Chen, Wei?gong Zhang, Xiao?na Zhang, "Fuzzy neural control for unmanned robot applied to automotive test", Industrial Robot: An International Journal, vol.40, no.5, pp.450, 2013.
