Abstract
Fuzzy systems are widely known to be universal approximators. They are very widely used for identification of unknown systems and plants. In the field of control engineering, it is a general practice to control complex plants and systems. But this requires the knowledge about the exact structure of the plant or the system to be controlled or analyzed. But in most of the practical cases, this is not available. Identification is a process to determine the structure of unknown plants and systems. Fuzzy systems, when used as approximators, mimic the plant and learn how to behave exactly like the plant. This learning process requires updation of the fuzzy parameters, so that ultimately the fuzzy system starts behaving exactly like the unknown plant. This paper discusses a very recent and popular scheme of optimization called ‘Intelligent Water Drop (IWD) Algorithm’. This algorithm is inspired by the nature and is based on intelligence of the drops of water present in nature. The paper demonstrates with examples the actual implementation procedure of the IWD algorithm. Also, the results clearly show that the fuzzy system optimized using IWD algorithm successfully identifies unknown complex plants and systems.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Narendra, K. S., Parthasarathy, K.: Identification and control of dynamical systems using neural networks. IEEE Trans. Neural Netw. 1(1), 4–27 (1990)
Takagi, T., Sugeno, M.: Fuzzy identification of systems and its applications to modeling and control. IEEE Trans. Syst. Man Cybern. 1, 116–132 (1985)
Lee, C.-H., Teng, C.-C.: Identification and control of dynamic systems using recurrent fuzzy neural networks. IEEE Trans. Fuzzy Syst. 8(4), 349–366 (2000)
Juang, C.-F.: A TSK-type recurrent fuzzy network for dynamic systems processing by neural network and genetic algorithms. IEEE Trans. Fuzzy Syst. 10(2), 155–170 (2002)
Martinez, D., Valdez, F.: An improved intelligent water drop algorithm to solve optimization problems. In: Melin, P., Castillo, O., Kacprzyk, J. (eds.) Design of Intelligent Systems Based on Fuzzy Logic, Neural Networks and Nature-Inspired Optimization. Studies in Computational Intelligence, vol. 601. Springer, Cham (2015)
Hartmut, S., Maniadakis, M.: Learning feed-forward and recurrent fuzzy systems: a genetic approach. J. Syst. Archit. 47(7), 649–662 (2001)
Shah-Hosseini, H.: The intelligent water drops algorithm: a nature-inspired swarm-based optimization algorithm. Int. J. Bio-Inspired Comput. 1(1–2), 71–79 (2009)
Alijla, B.O., Wong, L.P., Lim, C.P., Khader, A.T., Al-Betar, M.A.: A modified intelligent water drops algorithm and its application to optimization problems. Expert Syst. Appl. 41(15), 6555–6569 (2014)
Vajdi, A., Zhang, G., Wang, Y., Zhao, Y., Liu, D., Wang, T.: A new approach based on intelligent water drops algorithm for node selection in service-oriented wireless sensor networks. In: 2014 IEEE Fourth International Conference on Big Data and Cloud Computing (BdCloud). IEEE, pp. 33–40 (2014)
Crawford, B., Soto, R., Astorga, G., OlguÃn, E.: Intelligent water drop algorithm (IWD) to solve software project scheduling problem. In: 2016 11th Iberian Conference on Information Systems and Technologies (CISTI). IEEE, pp. 1–4 (2016)
Gorrini, V., Bersini, H.: Recurrent fuzzy systems. In: Proceedings of the Third IEEE Conference on Fuzzy Systems, 1994. IEEE World Congress on Computational Intelligence, pp. 193–198. IEEE (1994)
Lin, C.-T., George Lee, C.S.: Neural Fuzzy Systems. PTR Prentice Hall, Upper Saddle River (1996)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Dass, A., Srivastava, S., Gupta, M. (2019). Identification of Dynamic Systems Using Intelligent Water Drop Algorithm. In: Malik, H., Srivastava, S., Sood, Y., Ahmad, A. (eds) Applications of Artificial Intelligence Techniques in Engineering . Advances in Intelligent Systems and Computing, vol 697. Springer, Singapore. https://doi.org/10.1007/978-981-13-1822-1_34
Download citation
DOI: https://doi.org/10.1007/978-981-13-1822-1_34
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-1821-4
Online ISBN: 978-981-13-1822-1
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)