Variability of hue and saturation components is an important drawback for developing accurate color image segmentation algorithms based on HSI spaces: different colors can return similar color components because of th...
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Variability of hue and saturation components is an important drawback for developing accurate color image segmentation algorithms based on HSI spaces: different colors can return similar color components because of the different illumination levels, and the components of a color change accordingly to the illumination level. To avoid these problems within color segmentation algorithms, we propose a method that, based on predicted hue and saturation deviations, provides the reliability degree of the H-S color components based obtained HIS values. The reliability degree has been used for improving color classification results
With easily available prior knowledge, we explore a new approach for nulling of reverberation through separating active sonar data into reverberation and moving target echo. From the perspective of signal processing, ...
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This paper presents the development of a maximum power point tracking algorithm using an artificial neural network for a solar power system. By applying a three layers neural network and some simple activation functio...
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This paper presents the development of a maximum power point tracking algorithm using an artificial neural network for a solar power system. By applying a three layers neural network and some simple activation functions, the maximum power point of a solar array can be efficiently tracked. The tracking algorithm integrated with a solar-powered battery charging system has been successfully implemented on a low-cost PIC16F876 RISC-microcontroller without external sensor unit requirement. The experimental results with a commercial solar array show that the proposed algorithm outperforms the conventional controller in terms of tracking speed and mitigation of fluctuation output power in steady state operation. The overall system efficiency is well above 91%
This paper deals with the data-driven design of observer based FDI systems. The basic idea is to identify parity space and the related matrices, instead of a state space model of the process under consideration, direc...
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This paper deals with the data-driven design of observer based FDI systems. The basic idea is to identify parity space and the related matrices, instead of a state space model of the process under consideration, directly from test data. The proposed method can be used for the data-driven design of parity space, observer and kalman filter based FDI systems.
In avionics and automotive applications of computing, special care must be taken of issues related to safety. Assurance must be provided that computer hardware or software does not contribute to situations, which may ...
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In avionics and automotive applications of computing, special care must be taken of issues related to safety. Assurance must be provided that computer hardware or software does not contribute to situations, which may cause loss of life or significant property damage. One aspect of this concern is the design of databuses, which provide a medium to exchange information among various electronics devices in a vehicle. Unfortunately, only a few aspects of bus design have been sufficiently covered in the research studying system safety. This paper reviews and compares available information on bus specifications. Databuses are discussed regarding their properties, such as signal characteristics and bus protocols, with respect to safety.
In this paper, a model-based scheme is presented for the detection and isolation of sensor faults in the vehicle lateral dynamics control systems. Core of the scheme is the handling of model uncertainties. This scheme...
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In this paper, a model-based scheme is presented for the detection and isolation of sensor faults in the vehicle lateral dynamics control systems. Core of the scheme is the handling of model uncertainties. This scheme has been successfully tested using real driving data.
In robotic operations where a manipulator is involved, it is well-known that the quantities measured by a wrist force/torque sensor are corrupted by the dynamics of the end effector and manipulator. To solve this prob...
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In robotic operations where a manipulator is involved, it is well-known that the quantities measured by a wrist force/torque sensor are corrupted by the dynamics of the end effector and manipulator. To solve this problem, an observer, which fuses information from force sensors and accelerometers, was designed recently in order to estimate the contact force exerted by a manipulator to its environment [1]. This paper introduced a high-speed, high-accuracy, versatile, simple, and fully autonomous technique for the calibration of this robotic manipulator 3D force observer by means of active motion. To verify the improvement, an impedance control scheme was used. A dynamic model of the robot-grinding tool using the new sensors was obtained by system identification. The experiments were carried out on an ABB industrial robot with open control system architecture.
This paper explores feedback controller design for cavity flows based on reduced-order models derived using Proper Orthogonal Decomposition (POD) along with Galerkin projection method. Our preliminary analysis shows t...
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This paper explores feedback controller design for cavity flows based on reduced-order models derived using Proper Orthogonal Decomposition (POD) along with Galerkin projection method. Our preliminary analysis shows that the equilibrium of the POD model is unstable and a static output feedback controller cannot stabilize it. We develop Linear Quadratic (LQ) optimal state feedback controllers and LQ optimal observers for the linearized models. The linear controllers and observers are applied to the nonlinear system using simulations. The controller robustness is numerically tested with respect to different POD models generated at different forcing frequencies. An estimation for the region of attraction of the linear controllers is also provided.
This paper deals with the implementation of Haar wavelet to the optimal control of linear singularly perturbed systems. The approximated composite control and the slow and fast trajectories with respect to a quadratic...
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This paper deals with the implementation of Haar wavelet to the optimal control of linear singularly perturbed systems. The approximated composite control and the slow and fast trajectories with respect to a quadratic cost function by solving only the linear algebraic equations are calculated. The results are illustrated with a simple example.
This paper deals with modelling and adaptive output tracking of a Transverse Flux Permanent Magnet Machine (TFPM) as a non-linear system with unknown nonlinearities by utilizing High Gain Observer (HGO) and Radial Bas...
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This paper deals with modelling and adaptive output tracking of a Transverse Flux Permanent Magnet Machine (TFPM) as a non-linear system with unknown nonlinearities by utilizing High Gain Observer (HGO) and Radial Basis Function (RBF) networks. The technique of feedback linearization and H ∞ control are used to design an adaptive control law for compensating the unknown nonlinearity parts, such the effect of cogging torque, as a disturbance is decreased onto the rotor angle and angular velocity tracking performances. Finally, the capability of the proposed method is shown in the simulation results.
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