1,721,068 research outputs found
Foreword. Proceedings of the 14th IFAC Conference on Control Applications in Marine Systems, Robotics, and Vehicles, CAMS 2022, Kongens Lyngby
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Augmenting robot intelligence via EEG signals to avoid trajectory planning mistakes of a smart wheelchair
Full text linkAssistive robots operate in complex environments and in presence of human beings, but the interaction between them can be affected by several factors, which may lead to undesired outcomes: wrong sensor readings, unexpected environmental conditions, or algorithmic errors represent just a few examples of the possible scenarios. When the safety of the user is not only an option but must be guaranteed, a feasible solution is to rely on a human-in-the-loop approach, e.g., to monitor if the robot performs a wrong action during a task execution or environmental conditions affect safety during the human-robot interaction, and provide a feedback accordingly. The present paper proposes a human-in-the-loop framework to enable safe autonomous navigation of an electric powered and sensorized (smart) wheelchair. During the wheelchair navigation towards a desired destination in an indoor scenario, possible problems (e.g. obstacles) along the trajectory cause the generation of electroencephalography (EEG) potentials when noticed by the user. These potentials can be used as additional inputs to the navigation algorithm in order to modify the trajectory planning and preserve safety. The framework has been preliminarily tested by using a wheelchair simulator implemented in ROS and Gazebo environments: EEG signals from a benchmark known in the literature were classified, passed to a custom simulation node, and made available to the navigation stack to perform obstacle avoidance
Reduced-Order Quadratic Kalman-like Filtering for Non-Gaussian Systems
No full textIn this paper the state estimation problem for linear discrete-time systems with non-Gaussian state and output noises is treated. In order to obtain a state optimal quadratic estimate with a lower computational effort and without loosing the stability, only the observable part of the second-order power system will be considered. The novelty of the proposed algorithm is to provide a method to compute, in a closed form, the rank of the observability matrix for the quadratic system. Considering a new augmented state-space built as the aggregate of the actual state vector and the observable components of the system squared state, and defining a new observation sequence composed of the original output measurements together with their square values, we will be in a condition to use Kalman filtering that, in this case, produces a suboptimal quadratic stable state estimate for the original system. The solution is given in closed form by a recursive algorithm
Optimal error governor for PID controllers
Full text linkError Governor (EG) deals with the problem of dynamically modifying the feedback error driving a controller having bounded control signals, for preventing controller or actuators saturation, avoiding integrator and/or slow dynamics windup and preserving the nominal linear controller behaviour. In this paper, an optimisation-based EG scheme is proposed for discrete-time Proportional-Integral-Derivative (PID) controllers driving Single-Input Single-Output (SISO) plants. The PID controller is considered in state-space form, and this formulation is used to pose the EG problem as a constrained quadratic programme (QP). Because the QP problem is subject to inequality constraints related to controller saturation, in order to use the proposed scheme in real-world applications, it should be necessary to consider appropriate algorithms for efficiently solving the optimisation problem. An efficient way to efficiently compute the solution of the EG problem is presented, reducing the computational effort required to solve the EG QP for using the proposed scheme in real control loops with high sampling rate. An analysis of control performance and computational burden is provided, comparing in simulation studies the optimal EG scheme performance with respect to control results provided by saturated PID with and without anti-windup action
Arc fault detection and appliances classification in AC home electrical networks using recurrence quantification plots and image analysis
Full text linkThis paper presents a method for the detection of series arc faults in electrical circuits, which has been developed starting from the recurrence quantification plots that allow to quantify the periodic behavior of time-series and to analyze the recurrences of a dynamical system presented by its phase space trajectory. Starting from this, the authors have found that it is possible to exploit recurrence quantification plots by using the gray-level co-occurrence matrix from which the extracted textural image features represent a proper set of indicators for suitably detecting arc faults. The database of this research is collected from 13 different types of load according to IEC 62606 standard. The proposed method's effectiveness is shown by means of experimental tests, which were carried out in both arcing and non-arcing conditions and in the presence of different loads
Special issue on advancements in ambient assisted living: integrating technology and human-centered design for enhancing user well-being and care
No full textA Coordination Architecture for UUV Fleets
No full textThis paper presents a modular and expandable architecture, which includes diversified functions and can be applied to heterogeneous fleets of unmanned underwater vehicles (UUVs), to solve the problem of decentralized formation coordination. The architecture is modular and each module is built such that it can solve a precise task using one or more functions. Three functions among them play a key role for the whole architecture: localization, faultless formation control and fault tolerance. The localization function is performed by the use of an adaptive extended Kalman filter (A-EKF) algorithm; the fault-free formation control function is based on a nonlinear decentralized model predictive control (ND-MPC) algorithm; the fault tolerance function is based on a hierarchy graph theory. The novelty of the paper lies in the use of the above mentioned functions as the core of an architecture which is expandable, decentralized and can be applied to a wide range of vehicles
A Detection-Estimation Approach to Filtering for Gaussian Systems with Intermittent Observations
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