In this paper we propose a model to represent and manage affective / emotional feedback. This model represents a set of emotions which is assumed to play a major role for learning processes. The emotions are to be identified during the learning phase. To achieve these objectives, we have considered primarily: i) Methods and techniques to assess and identify affectivity/ emotivity in ITS (Intelligent Tutoring System), ii) Feedback management derived by the detection of user's affective states in ITS. Our objective is to establish a methodology through the steps that lead us to 'identification and quantification of the emotional state of a learner. © 2012 Crown Copyright

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Controller design for autonomous 4-wheeled ground vehicles is performed with differential flatness theory. Using a 3-DOF nonlinear model of the vehicle's dynamics and through the application of differential flatness theory an equivalent model in linear canonical (Brunovksy) form is obtained. For the latter model a state feedback controller is developed that enables accurate tracking of velocity setpoints. Moreover, it is shown that with the use of Kalman Filtering it is possible to dynamically estimate the disturbances due to unknown forces and torques exerted on the vehicle. The processing of velocity measurements (provided by a small number of on-board sensors) through a Kalman Filter which has been redesigned in the form of a disturbance observer results in accurate identification of external disturbances affecting the vehicle's dynamic model. By including in the vehicle's controller an additional term that compensates for the estimated disturbance forces, the vehicle's motion characteristics remain unchanged. Numerical simulation confirms the efficiency of both the proposed controller and of the disturbance forces estimator.