Exploiting structure in piecewise affine identification of LFT systems

Identification of interconnected systems is a challenging problem in which it is crucial to exploit the available knowledge about the interconnection structure. In this paper, identification of discrete-time nonlinear systems composed by interconnected linear and nonlinear systems, is addressed. An iterative identification procedure is proposed, which alternates the estimation of the linear and the nonlinear components. Standard identification techniques are applied to the linear subsystem, whereas recently developed piecewise affine (PWA) identification techniques are employed for modelling the nonlinearity. A numerical example analyzes the benefits of the proposed structure-exploiting identification algorithm compared to applying black-box PWA identification techniques to the overall system

Periodic Model Predictive Control for Tracking Halo Orbits in the Elliptic Restricted Three-Body Problem

A periodic model predictive control (MPC) scheme is proposed for tracking halo orbits. The problem is formulated and solved in the elliptic restricted three-body problem (ER3BP) setting. The reference trajectory to be tracked is designed by using eccentricity continuation techniques. The MPC design exploits the periodicity of the tracking model and guarantees exponential stability of the linearized closed-loop system, through a suitable choice of the terminal set and weight matrices. A sum-of-norms cost function is adopted to promote fuel saving. The proposed control scheme is validated on two simulated missions in the Earth-Moon system, which, respectively, involve station keeping on a halo orbit near the L1 Lagrange point and rendezvous to a halo orbit near the L2 Lagrange point. Results illustrate the advantage of designing the reference trajectory and the periodic control directly in the ER3BP setting versus approximate solutions based on the circular restricted three-body problem (CR3BP)

In-Cylinder Pressure Estimation from Rotational Speed Measurements via Extended Kalman Filter

Real-time estimation of the in-cylinder pressure of combustion engines is crucial to detect failures and improve the performance of the engine control system. A new estimation scheme is proposed based on the Extended Kalman Filter, which exploits measurements of the engine rotational speed provided by a standard phonic wheel sensor. The main novelty lies in a parameterization of the combustion pressure, which is generated by averaging experimental data collected in different operating points. The proposed approach is validated on real data from a turbocharged compression ignition engine, including both nominal and off-nominal working conditions. The experimental results show that the proposed technique accurately reconstructs the pressure profile, featuring a fit performance index exceeding 90% most of the time. Moreover, it can track changes in the engine operating conditions as well as detect the presence of cylinder-to-cylinder variations

Upper Body Pose Estimation Using Wearable Inertial Sensors and Multiplicative Kalman Filter

Estimating the limbs pose in a wearable way may benefit multiple areas such as rehabilitation, teleoperation, human-robot interaction, gaming, and many more. Several solutions are commercially available, but they are usually expensive or not wearable/portable. We present a wearable pose estimation system (WePosE), based on inertial measurements units (IMUs), for motion analysis and body tracking. Differently from camera-based approaches, the proposed system does not suffer from occlusion problems and lighting conditions, it is cost effective and it can be used in indoor and outdoor environments. Moreover, since only accelerometers and gyroscopes are used to estimate the orientation, the system can be used also in the presence of iron and magnetic disturbances. An experimental validation using a high precision optical tracker has been performed. Results confirmed the effectiveness of the proposed approach

Si and Sn doping of ε-Ga2O3 layers

Low resistivity n-type e-Ga2O3 epilayers were obtained for the first time either by adding silane to the gas phase during the metal organic vapour phase epitaxy deposition or by diffusing Sn in nominally undoped layers after the growth. The highest doping concentrations were few 1018 cm−3 and about 1017 cm−3 for Si and Sn doping, with corresponding resistivity below 1 and 10 Ω cm, respectively. Temperature dependent transport investigation in the range of 10-600 K shows a resistivity behavior consistent with the Mott law, suggesting that conduction through localized states dominates the electrical properties of Si- and Sn-doped samples. For both types of dopants, two different mechanisms of conduction through impurity band states seem to be present, each of them determining the transport behavior at the lower and higher temperatures of the measurement range.Low resistivity n-type e-Ga2O3 epilayers were obtained for the first time either by adding silane to the gas phase during the metal organic vapour phase epitaxy deposition or by diffusing Sn in nominally undoped layers after the growth. The highest doping concentrations were few 1018 cm−3 and about 1017 cm−3 for Si and Sn doping, with corresponding resistivity below 1 and 10 Ω cm, respectively. Temperature dependent transport investigation in the range of 10-600 K shows a resistivity behavior consistent with the Mott law, suggesting that conduction through localized states dominates the electrical properties of Si- and Sn-doped samples. For both types of dopants, two different mechanisms of conduction through impurity band states seem to be present, each of them determining the transport behavior at the lower and higher temperatures of the measurement range