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To deal with the rigid template matching problem in real-world scenarios, we propose a novel iterative feature-pair updating framework which is also robust to high levels of outliers, such as background changing, complex nonrigid deformation and partial occlusion. Given a pair of template image and target image, we first extract a set of corresponding feature-pairs as candidates. Then, we propose...
The deployment of Wireless Sensor Networks to support optimal coverage is obviously a fastidious task, especially in hard to reach or inaccessible area. To address this problem, simplifying assumptions and simulations are commonly used techniques. However, these techniques may not be able to capture all the details about the problem to be solved. Hence, transition from the simulation to the actual...
The robot manipulators are an extremely nonlinear MIMO and highly coupled system. Further, the performances of the controlled systems are adversely affected by the existence of model uncertainties and disturbances. Therefore, the controller design for robotic systems is a difficult task for controller developer. In this paper, a novel application of the artificial bee colony (ABC) algorithm to optimize...
How to design an optimal mixed H2/H∞ robust FID controller for a complex control system is of great practical importance, but it is still an open issue. From the perspective of evolutionary algorithm, this paper formulates this issue firstly as a typical constrained optimization problem by minimizing a weighted objective function consisting of the robust stability performance, disturbance attenuation...
In robotics, non-linear least squares estimation is a common technique for simultaneous localization and mapping. One of the remaining challenges are measurement outliers leading to inconsistency or even divergence within the optimization process. Recently, several approaches for robust state estimation dealing with outliers inside the optimization back-end were presented, but all of them include...
This paper presents a new method for designing the weights used for development of robust controllers for a quadrotor model with parameter uncertainty. The weights alongside the controllers are developed for attitude and altitude tracking by resolving a constrained non-linear minimization problem formulated over the conventional mixed sensitivity optimization S over T method. The optimization routine...
Power system stabilizer (PSS) is extensively used to enhance the angular stability by providing damping to the generator's oscillation. An electric torque is enforced in the rotor shaft in phase with the speed variation to provide this damping. In this paper a PSO based Robust Power System Stabilizer (RPSS) design has been proposed depending upon mixed sensitivity based H output feedback control in...
This paper is concerned with the problem of finite-time H2/H∞ control for linear stochastic systems. First, a new definition of finite-time H2/H∞ control is given. Second, some sufficient conditions for the existence of finite-time H2/H∞ control are obtained, and the relationships among transient performance, H2 performance index and H00 performance index are represented by an algorithm. Finally,...
A robust model predictive control approach for a class of uncertain continuous systems with nonlinear disturbance and state-delay is proposed. The designed robust controller guarantees the closed-loop system asymptotically stable and the receding horizon performance index online minimum. Based on receding optimization principle of predictive control, the infinite time domain optimization problem is...
This paper studies a formation control problem for multiple mobile robot systems with model uncertainty. The formation is achieved by a distributed robust predictive control algorithm. Firstly, a distributed model of the formation system is derived by using the path tracking error dynamic of single mobile robot. Considering the error of linearization and measurement error caused by the accelerometer...
Deep learning has achieved great success in face recognition, however deep-learned features still have limited invariance to strong intra-personal variations such as large pose changes. It is observed that some facial attributes (e.g. eyebrow thickness, gender) are robust to such variations. We present the first work to systematically explore how the fusion of face recognition features (FRF) and facial...
In this paper, we study matrix scaling and balancing, which are fundamental problems in scientific computing, with a long line of work on them that dates back to the 1960s. We provide algorithms for both these problems that, ignoring logarithmic factors involving the dimension of the input matrix and the size of its entries, both run in time \widetilde{O}(m\log \kappa \log^2 (1/≥ilon))...
The visual and automatic classification of vehicles plays an important role in the Transport Area. Besides of security issues, the monitoring of the type of traffic in streets and highways, as well the traffic dynamics over time, allows the optimization of use and of resources related to such public infrastructure. In this work we propose a novel method, called 2D-DBM, for robust and efficient automatic...
To deal with the increasing penetration of uncertainties caused by renewable generations and uncertain loads, this paper proposes a novel robust optimization model for the optimal power flow (OPF) problem of power systems. In the model proposed, the generation and the network topology are co-optimized, and then the proposed robust optimal power flow with transmission switching (ROPF_TS) model is converted...
In order to reduce the online calculation amount and improve the response speed, this paper proposes a robust model predictive control algorithm for nonlinear uncertain systems based on linear matrix inequality (LMI). The algorithm is divided into two parts: offline algorithm and online algorithm. In the offline algorithm, a sequence of asymptotically stable invariant ellipsoids and the corresponding...
Although several powerful joint filters for cross-modal image pairs have been proposed, the existing joint filters generate severe artifacts when there are misalignments between a target and a guidance images. Our goal is to generate an artifact-free output image even from the misaligned target and guidance images. We propose a novel misalignment-robust joint filter based on weight-volume-based image...
The well-known maximum torque per ampere (MTPA) strategy is usually integrated the field oriented control (FOC) to improve the efficiency of interior permanent-magnet (IPM) synchronous motor drives. As an alternative to the FOC, direct torque control (DTC) has attracted extensive attention from both academia and industry in the last few decades, due to its distinctive advantages, e.g., fast dynamic...
The traditional affine iterative closest point (ICP) algorithm is fast and accurate for affine registration between two point sets, but it is easy to fall into local minimum. This paper proposes a robust Affine ICP algorithm based on corner points. First, an objective function is established under the guidance of corner points, where the corner points as the shape control point guides the affine registration...
Owing to its simplicity and efficacy, orthogonal matching pursuit (OMP) has been a popular sparse representation method for compressed sensing and pattern classification. As a recent extension of OMP, generalized OMP (GOMP) improves the efficiency of OMP by identifying multiple atoms each iteration. Nonetheless, GOMP utilizes the mean square error (MSE) criterion as the loss function, which has been...
In this paper, the problem of target localization in the presence of outlying sensors is tackled. This problem is important in practice because in many real-world applications the sensors might report irrelevant data unintentionally or maliciously. The problem is formulated by applying robust statistics techniques on squared range measurements and two different approaches to solve the problem are...
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