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In: 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 (2010). Valdez, F., Melin, P., Castillo, O.: Fuzzy control of parameters to dynamically adapt the PSO and GA Algorithms. In: 2007 IEEE Congress on Evolutionary Computation, CEC 2007, pp. Ītashpaz-Gargari, E., Lucas, C.: Imperialist competitive algorithm: An algorithm for optimization inspired by imperialistic competition. Yang, X.S.: Nature-Inspired Optimization Algorithms. Izadbakhsh, A.: FAT-based robust adaptive control of electrically driven robots without velocity measurements. Zadeh, L.A.: Outline of a new approach to the analysis of complex systems and decision processes. Springer Science and Business Media Deutschland GmbH (2021). In: Studies in Computational Intelligence, pp. John Wiley & Sons, Hoboken (2007)Īmézquita, L., Castillo, O., Soria, J., Cortes-Antonio, P.: A novel study of the multi-verse optimizer and its applications on multiple areas of computer science. Įngelbrecht, A.P.: Computational Intelligence: An Introduction.

Teodorović, D.: Bee colony optimization (BCO).

Mirjalili, S., Mirjalili, S.M., Lewis, A.: Grey wolf optimizer. Mirjalili, S., Mirjalili, S.M., Hatamlou, A.: Multi-verse optimizer: a nature-inspired algorithm for global optimization.

Jang, J.S.R., Sun, C.T., Mizutani, E.: Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence. Wescott, T.: Applied control theory for embedded systems. The objective of this study is to observe the behavior of the multi-verse optimizer over control systems and its promising uses on more complex fuzzy control systems.

The fuzzy system that controls this problem uses two inputs and two outputs, where the optimization occurs over the antecedent and consequent membership functions, this by only changing the parameters of the main points in every membership function. For the main application of the study, we use a common control problem which is the temperature control in a shower, where its control objective is to achieve and maintain a desired temperature and flow, this by controlling the opening and closing speed of the cold and hot water valves. In this paper we study the application of metaheuristics in optimization of fuzzy logic controllers, mainly with the multi-verse optimizer and the comparison with other algorithms like PSO.