A novel approach for optimization of nozzle angle and thrust vectoring controller via a sub-mutation genetic algorithm - Catalbas, Mehmet Cem; Gulten, Arif (ICIC International, 2017)
In this paper, we present a method for a proportional-integral-derivative (PID) controller design via new and improved genetic algorithm approach. This method provides for determining optimal controller parameters about ballistic missile systems. The relationship between thrust vector and angle of the nozzle is examined. This relationship is vital for controlling the movements of ballistic missiles. PID controller system provides sufficient success as observed in the results. In this study, optimal PID controller parameters are obtained by a new approach which is called as a sub-mutation genetic algorithm. The sub-mutation genetic algorithm provides more successful and robust results than that of the traditional genetic algorithm. © 2017 ICIC International.
Keywords: Ballistic missile; Genetic algorithm (GA); Nozzle; Optimal controller design; Optimization; Thrust vectoring