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Using Augmented Reality (AR) could offer stimuli to rehabilitation from neuro-motor disorders, since the patient can be aided in a better known reality than Virtual Reality (VR). The main goal for an AR system is to achieve a good quality of tracking the real object to align with virtual contents. Often a single sensor could not provide enough information to that end due to a low updating rate; therefore joining an other high updating rate sensor could be indispensable, but how to combine data from different sensors especially when they work all at different rates? In this paper an approach based on recursive parameter estimation, focusing on multi-rate tracking in AR devices is suggested. The system of this study has a multi-sensor configuration provided by a webcam and a 3-Axis MEMS inertial sensor, both working at different sample rates. Also an augmented reality application, designed for the neuro-motor rehabilitation of the upper limb, has been developed and shown.

This paper considers the problem of designing an observer for navigation and localization of inertial systems. Since the measurement systems used in this field have a low update rate with respect to the control algorithm, the design of a suitable observer with sampled measurements is required. Here a hybrid non-linear observer is proposed, combining two different observers with different characteristics. A theoretical treatment is given in order to prove the convergence of the observer and it will be contextualized in the framework of the hybrid systems, providing an elegant setting for the proposed solution. Finally experimental results show the feasibility of the proposed observer and the good behaviors in terms of estimation error that can be achieved.

In this paper a wearable sensor system, consisting of accelerometers and gyros, has been studied to estimate hip and knee angles. The proposed algorithm, developed in order to avoid the error accumulation due to gyroscopes drift, has been tested on angle measurement of the hip and knee of a commercial device for assisted gait. The results have shown a good accuracy of the angles estimation, also in high angle rate movement

This paper deals with speed and rotor flux estimation of induction motors via Extended Kalman Filter (EKF). The filter is designed starting from a discrete time model obtained by means of a first order discretization of the original nonlinear model of the induction motor (IM). In order to obtain accurate estimation of the above mentioned variables, the load torque is included into the state variables and then estimated, thus constructing a sixth order EKF. Experimental results are shown with reference to a closed loop sensorless control system, consisting of a 750 W induction motor supplied by a voltage source inverter, a cascade controller consisting of four PI control loops and the designed EKF which gives the feedback variables. Comparison with a fifth order EKF, which does not include mechanical equation in the model, is carried out by means of simulation in Matlab/Simulink environment.

This paper deals with model-based robust control of DC/DC power electronic converters. The converter is modelled by means of its static characteristic and a few continuous-time linear and time-invariant (LTI) models corresponding to contiguous ranges of duty-cycle. The model appears as a Hammerstein model in which the values of the parameters of the LTI part depend on the actual duty-cycle operating range. This suggests to describe the converter as an uncertain system to be controlled using robust control techniques. Frequency domain approach is used for describing the nominal model and the uncertainty. In view of applying robust control, identification of the LTI models is performed by means of simulation experiments carried out on a converter switched model implemented on MATLAB-SIMULINK environment. Internal Model Control (IMC) structure is employed for the controller design, but its implementation is performed using the equivalent classical feedback control structure. Comparison with a PI controller, designed by means of phase margin assignment, shows the peculiarities of the proposed approach.

In this paper a model based control methodology is described with reference to a wind turbine for production of alternative energy. The mathematical model of a 600 kW wind turbine is taken into account assuming a well defined profile of the rotor blades. A set of reference angular speeds of the asynchronous generator and a set of reference pitch angles of the blade wind turbine are obtained in order to maximize the extracted wind power and to reach equilibrium conditions between the wind-generated torque and the electric torque of the generator. Finally a PID model based controller is designed and then tested by means of simulation experiments.

This paper deals with the robust control of a Hammerstein mathematical model of DC/DC converters, consisting of the nonlinear static characteristics of the converter followed by one of a few number of linear time- invariant models which describe the converter in the useful working range. One of these models is assumed as the nominal model of the system and the remaining models are used for describing the model uncertainty. Nominal behaviour is assured using H-2 optimal control method, Robust stability and behaviour are assured by imposing H-infin specifications. The closed loop control system consisting of the converter Hammerstein model and the robust controller is analyzed by means of simulation experiments.

This paper deals with a control strategies for underactuated underwater vehicles whose target is the tracking of a space trajectory. A cascade control strategy is employed which brings to a control law consisting of: 1) a kinematic control law, derived from the vehicle kinematic model, which forces this model to track the reference trajectory; and 2) a dynamic control law which forces the system to track the reference signals given by the kinematic control law. Conditions for asymptotic tracking of the trajectory are given with reference to the standard dynamical model of the above vehicle. An observer of the marine current is also added in order to process the control law. Simulation tests illustrate the proposed approach.

This paper deals with off-line identification of electrical and mechanical parameters of induction motors, using least square techniques. Two stator currents, three stator voltages and speed are acquired during an experimental test consisting of a start transient up to steady state and a stop transient from steady state to standstill. For identification, the acquired signals and their derivatives are filtered by means of digital anti-causal filters. The input-output behaviour obtained by means of simulation using the mathematical model with estimated parameters is compared with that detected experimentally with the aim of showing the validity of the approach described.

The problem of identification of a nonlinear vectorial function is studied using an approach based on the rough set and fuzzy logic theories. The rough set theory allows one to obtain a linguistic description of the function, whereas the fuzzy logic theory allows one to generate numerical values of the function starting from its linguistic description. Simulation experiments are shown regarding the identification of a two-variables sinc function.