Search results for "automatic"

Localization from inertial data and sporadic position measurements

2020

International audience; A novel estimation strategy for inertial navigation in indoor/outdoor environments is proposed with a specific attention to the sporadic nature of the non-periodic measurements. After introducing the inertial navigation model, we introduce an observer providing an asymptotic estimate of the plant state. We use a hybrid dynamical systems representation for our results, in order to provide an effective, and elegant theoretical framework. The estimation error dynamics with the proposed observer shows a peculiar cascaded interconnection of three subsystems (allowing for intuitive gain tuning), with perturbations occurring either on the jump or on the flow dynamics (depen…

Virtual Vehicles Manager: a Java Virtual Reality Environment for Distributed Multi Vehicles Dynamics Control and Simulation

2007

Predicting limiting 'free sugar' consumption using an integrated model of health behavior.

2020

Excess intake of ‘free sugars’ is a key predictor of chronic disease, obesity, and dental ill health. Given the importance of determining modifiable predictors of free sugar-related dietary behaviors, we applied the integrated behavior change model to predict free sugar limiting behaviors. The model includes constructs representing ‘reasoned’ or deliberative processes that lead to action (e.g., social cognition constructs, intentions), and constructs representing ‘non-conscious’ or implicit processes (e.g., implicit attitudes, behavioral automaticity) as predictors of behavior. Undergraduate students (N = 205) completed measures of autonomous and controlled motivation, the theory of planned…

Robust l2-gain control for 2D nonlinear stochastic systems with time-varying delays and actuator saturation

2013

Abstract This paper is concerned with the problems of stability analysis and l2-gain control for a class of two-dimensional (2D) nonlinear stochastic systems with time-varying delays and actuator saturation. Firstly, a convex hull representation is used to describe the saturation behavior, and a sufficient condition for the existence of mean-square exponential stability of the considered system is derived. Then, a state feedback controller which guarantees the resulting closed-loop system to be mean-square exponentially stable with l2-gain performance is proposed, and an optimization procedure to maximize the estimation of domain of attraction is also given. All the obtained results are for…

Use of accelerometers and gyros for hip and knee angle estimation

2013

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

Stability analysis for stochastic hybrid systems: A survey

2014

This survey addresses stability analysis for stochastic hybrid systems (SHS), which are dynamical systems that combine continuous change and instantaneous change and that also include random effects. We re-emphasize the common features found in most of the models that have appeared in the literature, which include stochastic switched systems, Markov jump systems, impulsive stochastic systems, switching diffusions, stochastic impulsive systems driven by renewal processes, diffusions driven by Lévy processes, piecewise-deterministic Markov processes, general stochastic hybrid systems, and stochastic hybrid inclusions. Then we review many of the stability concepts that have been studied, inclu…

Least squares and genetic algorithms for parameter identification of induction motors

2001

Abstract This paper deals with off-line parameter identification of induction motors by means of least square (LS) techniques and genetic algorithms (GA), using stator voltages, stator currents and velocity as input–output data. For analytical identification by LS algorithms, filtering of experimental data is performed by means of anticausal filters. Two models useful for identification are derived in which the products of acceleration and rotor fluxes, usually neglected, are taken into account. The GA-based identification method consists of the determination of the best parameters which match input–output behaviour of the motor. Both methods are investigated and compared by means of experi…

Probabilistic Self-Localization and Mapping - An Asynchronous Multirate Approach

2008

[EN] In this paper, we present a set of robust and efficient algorithms with O(N) cost for the solution of the Simultaneous Localization And Mapping (SLAM) problem of a mobile robot. First, we introduce a novel object detection method, which is mainly based on multiple line fitting method for landmark detection with regular constrained angles. Second, a line-based pose estimation method is proposed, based on LeastSquares (LS). This method performs the matching of lines, providing the global pose estimation under assumption of known Data-Association. Finally, we extend the FastSLAM (FActored Solution To SLAM) algorithm for mobile robot self-localisation and mapping by considering the asynchr…

Characterization of MEMS accelerometer self-noise by means of PSD and Allan Variance analysis

2017

In this paper, we have studied the sources of error of a low-cost 3-axis MEMS accelerometer by means of Power Spectral Density and Allan Variance techniques. These techniques were applied to the signals acquired from ten identical devices to characterize the variability of the sensor produced by the same manufacturer. Our analysis showed as identically produced accelerometer have somehow variable behavior in particular at low frequency. It is therefore of paramount importance before their use in Inertial Navigation or Earthquakes Monitoring System, a complete characterization of each single sensors.

Robust Discrete-Time Lateral Control of Racecars by Unknown Input Observers

2023

This brief addresses the robust lateral control problem for self-driving racecars. It proposes a discrete-time estimation and control solution consisting of a delayed unknown input-state observer (UIO) and a robust tracking controller. Based on a nominal vehicle model, describing its motion with respect to a generic desired trajectory and requiring no information about the surrounding environment, the observer reconstructs the total force disturbance signal, resulting from imperfect knowledge of the time-varying tire-road interface characteristics, presence of other vehicles nearby, wind gusts, and other model uncertainty. Then, the controller actively compensates the estimated force and as…