This Matlab toolbox provides the features to generate the optimized fuzzy model (Mamdani or Sugeno) from the available data automatically using Particle Swarm Optimization (PSO) algorithm.
The PSO method is a member of the broad category of swarm intelligence techniques for finding optimized solutions. The motivation behind the PSO algorithm is the social behavior of animals viz. flocking of birds and fish schooling. The PSO has its origin in simulation for visualizing the synchronized choreography of bird flock, which later on was modified to be used for optimization.
Fuzzy systems, which are rule-based systems, are being used for complex systems problems, where it is extremely difficult to describe the system mathematically and are being used successfully in many areas. This tool will help the developers build these systems in a very short time.
Important:The code has been written for fuzzy model identification of Nickel-Cadmium (Ni-Cd) rapid battery charger designed by our project team. The purpose of development of rapid Ni-Cd battery charger was to reduce the charging time by using higher charging current, but not at the cost of damage to batteries. The code can be easily modified by the users of this toolbox for their applications.
