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Object-branch coverage (OBC) is often used as a measure of the thoroughness of tests suites, augmenting or substituting source-code based structural criteria such as branch coverage and modified condition/decision coverage (MC/DC). In addition, with the increasing use of third-party components for which source-code access may be unavailable, robust object-code coverage criteria are essential to assess...
This paper presents a generalized iterative learning control (ILC) design in the frequency domain with experimental validation. The optimal ILC learning function and robustness filter function are simultaneously optimized by solving a linear programming problem using frequency response functions. Moreover, the design realizes an optimal trade-off between robust convergence, converged tracking performance,...
The paper present an architecture multi-controller based in conventional PID controller and robust Fractional PID controller (FOPID) using PSO algorithm to optimize the parameters of PID and FOPID, and improved the robustness. This approach applied to control robotics wrist (Robot RX-90 Staübli). A brief overview of the process with a non-linear and linear mathematical modeling of the process. Principle...
The operation scheduling is a crucial factor that can affect the economic and environmental benefits and operation reliability of the microgrids (MGs). However, widely used scheduling methods are lacking in the comprehensive consideration for the multi-objective (MO) property and robustness of the system operation. Also, the generated solutions might not diminish the disturbance of uncertainty under...
In industrial control, there are a large number of nonlinear strongly coupled controlled objects with external disturbance. It is difficult to control the object of such a good effect with classical control theory. Aiming at the problem of disturbance rejection, decoupling and tracking control of this kind of system, PIDNN controller is adopted in this paper, and its weight correction algorithm is...
In this paper we examine the effects of using object poses as guidance to learning robust features for 3D object pose estimation. Previous works have focused on learning feature embeddings based on metric learning with triplet comparisons and rely only on the qualitative distinction of similar and dissimilar pose labels. In contrast, we consider the exact pose differences between the training samples,...
Estimating the 6-DoF pose of a camera from a single image relative to a pre-computed 3D point-set is an important task for many computer vision applications. Perspective-n-Point (PnP) solvers are routinely used for camera pose estimation, provided that a good quality set of 2D-3D feature correspondences are known beforehand. However, finding optimal correspondences between 2D key-points and a 3D point-set...
With the aid of double-controller design concept and particle swarm optimization (PSO) algorithm, an internal model control (IMC) scheme with two-degree-of-freedom (TDF-IMC) based on PSO algorithm (PSO-TDF-IMC) is proposed, which is capable of controlling large time-delay processes. This method takes integral time absolute error (ITAE) index as objective function and uses PSO algorithm to optimize...
In this paper, the problem of input-to-state stability robust model predictive control(MPC) is studied for the discrete time uncertain singular system with input constrain and bounded disturbances. By constructing the ISS-Lyapunov function with the method of linear matrix inequality (LMIs), the “quasi-min-max” optimization problems are converted into finite time convex programming problems. Then the...
We present a new point set registration method with global-local correspondence and transformation estimation (GL-CATE). The geometric structures of point sets are exploited by combining the global feature, the point-to-point Euclidean distance, with the local feature, the shape distance (SD) which is based on the histograms generated by an elliptical Gaussian soft count strategy. By using a bidirectional...
We propose Stereo Direct Sparse Odometry (Stereo DSO) as a novel method for highly accurate real-time visual odometry estimation of large-scale environments from stereo cameras. It jointly optimizes for all the model parameters within the active window, including the intrinsic/extrinsic camera parameters of all keyframes and the depth values of all selected pixels. In particular, we propose a novel...
Deblurring images with outliers has attracted considerable attention recently. However, existing algorithms usually involve complex operations which increase the difficulty of blur kernel estimation. In this paper, we propose a simple yet effective blind image deblurring algorithm to handle blurred images with outliers. The proposed method is motivated by the observation that outliers in the blurred...
Similar to common object discovery in images or videos, it is of great interests to discover and locate common actions in videos, which can benefit many video analytics applications such as video summarization, search, and understanding. In this work, we tackle the problem of common action discovery and localization in unconstrained videos, where we do not assume to know the types, numbers or locations...
We present a robust algorithm for personalizing a spheremesh tracking model to a user from a collection of depth measurements. Our core contribution is to demonstrate how simple geometric reasoning can be exploited to build a shape-space, and how its performance is comparable to shape-spaces constructed from datasets of carefully calibrated models. We achieve this goal by first reparameterizing the...
Cloud scheduler manages multi-resources (e.g., CPU, GPU, memory, storage etc.) in cloud platform to improve resource utilization and achieve cost-efficiency for cloud providers. The optimal allocation for multi-resources has become a key technique in cloud computing and attracted more and more researchers' attentions. The existing multi-resource allocation methods are developed based on a condition...
In this paper, we propose an optimization model for planning a robust path against changes in traffic volume. Robustness is based on the form of the travel time function. The proposed model can be applied not only when traffic volume increases but also when it decreases. In addition, the proposed model can set the ratio of consideration by a parameter depending on whether the traffic volume is increasing...
Two novel hybridization schemes for the particle swarm repetitive controller (PSRC) are developed and tested herein. They are designed to be used in power electronic converters, such as grid-tie converters or constant-amplitude constant-frequency (CACF) true sine wave inverters, as well as in motion control systems, especially in assembly line robots. The proposed control algorithms combine the good...
This paper studies the performance of a fractional-order proportional integral derivative (FOPID) controller designed for parabolic distributed solar collectors. The control problem addressed in concentrated solar collectors aims at forcing the produced heat to follow a desired reference despite the unevenly varying solar irradiance. In addition to the unpredictable variations of the energy source,...
The presented work is motivated by Free Space Optics (FSO) communications. FSO is a well established wireless optical transmission technology considered as an alternative to radio communications for example in metropolitan wireless mesh networks. An FSO link is established by means of a laser beam between the transmitter and the receiver placed in the line of sight. A major disadvantage of FSO links...
In the paper, a new approach to the robust optimal design is proposed. The idea is to consider the sensitivity as an extra objective function which is cost-effective. The optimal design of a switched-reluctance motor is considered as the case study: since the case study exhibits two design criteria, the Pareto front trading off three objective functions is approximated by means of evolutionary computing.
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