Artificial Bee Colony Algorithm for Parametric Optimization of Spacecraft Attitude Tracking Controller

To satisfy the rapidly and accurately attitude tracking for spacecraft, artificial bee colony (ABC) algorithm is introduced to the controller parametric optimization of spacecraft attitude tracking. The spacecraft attitude tracking dynamics model, kinematics model and a sliding model controller using radial basis function neural network are build up. The concept of ABC algorithm is presented and the steps are also given. For the fitness function of ABC algorithm, the weighted index of error and angular velocity error with the simulation time are used. The optimization result compared between particle swarm optimization (PSO) and ABC algorithm shows the efficient of the ABC algorithm. The simulation result with the optimized controller shows that the controller could guarantee robustness against uncertainties and external disturbances increased.