关键词：蚁群优化算法；模糊控制器；仿真
摘 要：A study of the behavior and evaluation of the Ant Colony Optimization algorithm (ACO) in Type-1 and Type-2 Fuzzy Controller design is presented in this chapter. The main objective of the work is based on the main reasons in tuning membership functions for the optimization Fuzzy Controllers of the benchmark problem known as the Water Tank with the algorithm of Ant Colony Optimization. For the design of Type-1 and Type-2 Fuzzy Controllers for particular applications, the use of bio-inspired optimization methods have helped in the complex task of finding the appropriate values of the parameters and the structure of fuzzy systems. In this research we consider the application of ACO as the paradigm that aids in the optimal design of Type-1 and Type-2 Fuzzy Controllers. We also analyzed that in evaluating the uncertainty, the results in the simulation are better with Type-2 Fuzzy Controllers. Finally, provide a comparison of the different methods for the case of designing Type-1 and Type-2 Fuzzy Controllers with Ant Colony Optimization.