A. Kosari - Department of New Sciences and Technologies, University of Tehran, Iran
H. Jahanshahi - Department of New Sciences and Technologies, University of Tehran, Iran
A. A. Razavi - Department of New Sciences and Technologies, University of Tehran, Iran

In this paper, multi-objective optimization based on Genetic Algorithm is used to find the design variables of PID, fuzzy and new Fuzzy-PID controllers applying for a thrust vector control of CANSAT carrier system. Motion vector control is considered according to the dynamic governing equation of the system which is derived using Newton’s method and defined mission in delivering payload into the specific height and flight path angle. The cost functions of the system are position error from the set point and deviation of the vector angle of carrier system with carrier body, where these cost functions must be minimized simultaneously. Results demonstrate that this new Fuzzy-PID controller is superior to other controllers which are exerted in the thrust vector control of a CANSAT carrier system. This Fuzzy-PID is capable of doing the mission with decrease in settling time and rise time with respect to the convenient minimized objective function values.

Multi-objective optimization, Genetic Algorithm, PID-controller, Fuzzy controller, Fuzzy-PID controller, CANSAT carrier system