Abstract—To create robots able to generate expressive motions and improve human robot interaction (HRI). An innovative adaptive control system architecture for a robot arm is developed which can adapt the control parameters and motion trajectories according to the perception generated by the human, the environment, and the overall robot interaction. An adaptive fuzzy controller that maps environmental and HRI factors to the PAD emotional model (Pleasure, Arousal, and Dominance) is proposed. These PAD values are used to change the robot strategy to generate trajectories and control parameters, which are designed to express different emotional states. The robot motions are commanded by the Robust Generalized Predictive Controllers (RGPC), using optimization by Youla parameters, that involves robot regulation with adaptive motion. The optimization control uses an adaptive receding horizon designed according to the response of the human and environment interaction. This proposal allows to generate motions with more personalized characteristics for human robot interaction in a non-humanoid robots.