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This paper focuses on the development of a test platform for the capture of non-cooperative targets by an autonomous robotic manipulator. The paper describes the platform and subsystems involved in the capture operation with an emphasis on the vision system and controller. The vision system employs a custom algorithm, detecting the target, determining the quality of the lock and predicting the motion...
Assessment of blood flow velocity in Doppler images is of great importance in clinical studies and research. From the Doppler waveform envelope, numerous indices can be obtained, such as the pulsatility index, resistance index, and systolic/diastolic ratio, as well as acceleration of the blood through valves. The evaluation for the Doppler images is usually conducted offline and manually by the physicians...
Networked control systems (NCS) are an active area of research within control and estimation. Networked control systems have many advantages by comparison with the traditional ones. The fault detection problem is studied in this paper for a class of linear networked control systems (NCS) with communication delays. Aim is to generate residual signals which, in the fault free case, are supposed to be...
An estimation of the state and the unknown inputs of the reduced nonlinear model of an activated sludge process using the Extended Kalman Filter (EKF) is proposed. First, we present the reduced nonlinear model. This model contained five state variables and four unknown inputs. For satisfying the rank condition for the construction of an EKF, one unknown input has been approximated and the daily mean...
In this paper, a fault detection, identification and estimation approach has been developed for the condition monitoring of the electro-hydraulic actuator (EHA) system using the multiple-model (MM) estimation algorithm. The MM estimation algorithm makes use of the extended Kalman filter (EKF) technique to generate estimates of states and key physical parameters, which are related to faults in the...
Position and orientation estimation is one of the main problem in mobile robotics: to navigate and accomplish its job a mobile robot must know where is it. To this sake, we suppose that a set of wireless sensors are located on the operation field, which can measure distance and orientation of the robot, and are connected with the estimator by a wireless network. An extended Kalman filter has been...
LQG/Loop Transfer Recovery (LQG/LTR) technique based on Kalman filter as observer, has some difficulties in facing with non-minimum phase systems. The main problem is that the observer becomes unstable when the compensator recovers the target loop asymptotically. In this paper, we propose an optimal robust recoverable target loops for a boiler system. Using asymptotic time-scale eigenstructure assignment...
This paper presents a new approach for on-line identification of an exact affine model for single-input, single- output (SISO) processes with nonlinear and time-varying behaviors. For this purpose, a modified growing and pruning algorithm for radial basis function (MGAP-RBF) neural network is used for affine modeling of the SISO nonlinear and time-varying processes. The extended Kalman filter (EKF)...
A new method for constructing Kalman-type filters is proposed, which, in addition to classical models of stochastic processes generated by a white noise, also uses a more universal piecewise-polynomial description of signals with consideration of their continuity and smoothness, allowing observing constraints on their level. On the one hand, the description makes it possible to avoid difficulties...
This paper presents a navigation of an autonomous robot using simultaneous localization and mapping (SLAM) in outdoor environments. SLAM is a method in which localization and mapping are done simultaneously in an unknown environment without an access to a priori map. This paper introduces a probabilistic approach to a SLAM problem under Gaussian and non-Gaussian conditions and offers alternative solutions...
This paper deals with optimal recursive filtering for time-variant singular systems. The novelty of this paper is the functional developed to deduce this filter in which least squares and penalty functions approaches are combined in a unified way. The advantage of this new procedure will be emphasized in the paper. The nominal singular Kalman filter will be deduced in its most general formulation...
In this paper a nonlinear optimal controller has been designed for aerodynamic control during the reentry phase of the reusable launch vehicle (RLV). The controller has been designed based on a recently developed technique optimal dynamic inversion (ODI). For full state feedback the controller has required full information about the system states. In this work an extended Kalman filter (EKF) is developed...
Two typical indoor settings are considered, one based on laser range finder readings and the other one on the distances gathered by the robot from a set of artificial landmarks (e.g. RFID tags). It is shown, by comparing the performance of the Extended and of the Unscented Kalman filters, that only the first setting could require the definition of more specific non linear filtering algorithms, not...
The human vestibular system, consisting of the otolith and semicircular canals, provides valuable information about body motion and orientation in terms of angular velocity and translational acceleration. This article discusses the dynamic characteristics of these organs and the generated signals and proposes approaches to combine these signals to infer for the body angular velocity. This is the first...
This paper presents an efficient extended Kalman filter implementation of a single-camera visual simulataneous localization and mapping (vSLAM) algorithm, vSLAM is a novel algorithm for simultaneous localization and mapping problem widely studied in mobile robotics field. The algorithm is vision and odometry-based. The problem with the implementation of all SLAM algorithms is the state vector size...
A simple procedure to include state inequality constraints in the unscented Kalman filter is proposed. With this procedure, the information of active state constraints influences the state covariance matrix, resulting in better estimates. In a numerical example, the approach outperforms the extended Kalman filter implemented with constraint handling via ldquoclippingrdquo.
The main goal of this paper consists in the development of a new actuator fault-tolerant control dedicated to nonlinear systems. Based on the assumption that the nonlinear system is described by a finite number of interpolated linear time invariant models, the proposed method makes possible the faults compensation for the whole operating range through an extended interacting multiple model. Its principle...
The intra-logistics is constantly subject to technological developments and changes. In the field of warehousing in former times, articles were identified over bar code. Nowadays with the growing requirements for mobility and reliability increasingly radio technologies are employed to request information. Wireless sensor networks simplify the stock accounting through a decentralization of the data...
For sequential jumps detection, isolation and estimation in discrete-time stochastic linear systems, (A.S. Wilsky et al., 1976) have developed the generalized likelihood ratio (GLR) test. After each detection and isolation of one jump, the treatment of another possible jump is obtained by a direct state estimate and covariance incrementation of the Kalman filter originally designed on the jump-free...
Unmanned aerial vehicles (UAVs) are increasingly used in military and scientific research. UAVs rely on accurate location information for a variety of purposes including navigation, motion planning and control, and mission completion. UAV INS/GPS localization is generally used based on navigation filter. Extended Kalman filter is largely used to solve the problem of data fusion and localization, however,...
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