Fuzzy logic decision making for autonomous applications
There is growing in interest in the effectiveness of emulating human decision making and learning in modern aerospace applications. The following is an examination of several applications in which type 1 and 2 fuzzy logic has been utilized in artificial intelligence and machine learning problems to demonstrate their capabilities. In Fuzzy Logic Inferencing for PONG (FLIP), the effectiveness of type 1 logic is examined as an optimal controller for players in the game of PONG. Robotic collaboration is also developed as the PONG game was expanded into a multiplayer option. Collaborative Learning usingFuzzy Inferencing (CLIFF) is an extension of this PONG game,
however type-2 logic is used to create a robotic coach that optimizes its players to beat its opponent in a development of layered fuzzy learning. Precision Route Optimization using Fuzzy Intelligence (PROFIT) examines the use of fuzzylogic as an optimizer in an algorithmic solution to a modified Travelling Salesman Problem (TSP). The TSP is modified in a way to better mimic a real-life scenario where footprints must be visited instead of simply points, which gives an interesting complexity to the problem. Considering the successes associated with these research endeavors, it can be concluded that type 1 and 2 fuzzy logic are both interesting tools that can further the abilities of intelligent systems and machine learning algorithms
Related Fuzzy Logic Project Titles:
- Dynamic rule based approach to reduce power consumption of the fuzzy logic controller for embedded applications.
- Fuzzy logic rules modeling similarity-based strict equality.
- Robust adaptive type-2 fuzzy logic controller design for a flexible air-breathing hypersonic vehicle.
- Bimodal vowel recognition using fuzzy logic networks – naive approach.
- Edge-Detection Method for Image Processing Based on Generalized Type-2 Fuzzy Logic.
- T2FELA: Type-2 Fuzzy Extreme Learning Algorithm for Fast Training of Interval Type-2 TSK Fuzzy Logic System.
- A fuzzy logic system for demand-side load management in residential buildings.
- A novel approach to improve execution time performance of Medical image processing.
- Juzzy online: An online toolkit for the design, implementation, execution and sharing of Type-1 and Type-2 fuzzy logic systems.
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