The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
This paper presents a hierarchical structure to solve the discrete time consensus problem for a group of agents. All the agents are divided into a couple of groups, and a new notation, called group information is proposed, which indicates all the agents' states inside one group. For each agent, it receives the information not only from the agent neighbors in the same group, but also the group information...
This paper develops a sliding mode control (SMC) approach for a class of uncertain nonlinear systems with unmatched uncertainties/disturbances. The newly proposed method is based on a novel fixed-time convergent sliding mode disturbance observer which can estimate the unmatched disturbance in a fixed time (time whose upper estimate is independent of the initial conditions). By designing a novel sliding...
In this paper, the problem of adaptive fixed-time 6 degree-of-freedom (DOF) tracking control for spacecraft non-cooperative rendezvous in presence of the parameter uncertainties and external disturbances is investigated. Firstly, a new multilayer fixed-time sliding mode surface (MFSMS) is designed, and the setting time of the proposed surface can be estimated without the knowledge of the initial conditions...
The standard Iterative Closest Point (ICP) algorithm is a robust and efficient rigid registration algorithm for 3D point clouds. Nevertheless, its efficiency notably decreases when applied to a large transformation cases. In order to avoid this drawback and improve its performance, we propose a new 3-step approach based on ICP and point Cloud Projection, called ICP- CP, that both enhances the accuracy...
This paper presents a variable coefficient nonsingular fast terminal sliding mode (VCNFTSM) control method with the extended state observer (ESO) for a class of second-order uncertain SISO nonlinear systems subject to external disturbance. First, a new variable coefficient double exponential reaching law is combined with NFTSM surface function to get finite time fast convergence in both reaching phase...
A robust entry guidance law with finite time convergence is designed for drag-tracking in this paper. The bank angle is regarded as the control variable. First, a robust sliding mode control (SMC) method, which can guarantee the finite time convergence, is proposed for a class of nonlinear systems with uncertainties and disturbances. Then, after the drag dynamics is given, the finite time guidance...
Many computer vision problems are formulated as the optimization of a cost function. This approach faces two main challenges: (1) designing a cost function with a local optimum at an acceptable solution, and (2) developing an efficient numerical method to search for one (or multiple) of these local optima. While designing such functions is feasible in the noiseless case, the stability and location...
Over the last few years, the combination synchronization of chaotic system receives a special attention. This paper introduces the idea of combination synchronization into complex networks. Based on sliding mode control (SMC) principle, the finite-time combination synchronization (FTCS) of four uncertain complex networks which combining as the form of A+B+C-D is investigated. And there are unknown...
Iterative learning control (ILC) is an approach suitable for systems which repeatedly perform a tracking task over a fixed time interval. However little attention has been paid to the case of multiple input, multiple output (MIMO) systems. In this paper theoretical results are derived and establish a close link between increased interaction, reduced robustness, slower convergence and greater control...
This paper presents a novel approach for designing a composite controller that finite time simultaneously stabilizes two single input nonlinear Port-Controlled Hamiltonian (PCH) systems under disturbances. Firstly, using a single output feedback, two PCH systems are combined to generate an augmented PCH system based on the Hamiltonian structure properties. Then, a finite time disturbance observer...
Recent work has demonstrated the effectiveness of gradient descent for recovering low-rank matrices from random linear measurements in a globally convergent manner. However, their performance is highly sensitive in the presence of outliers that may take arbitrary values, which is common in practice. In this paper, we propose a truncated gradient descent algorithm to improve the robustness against...
Low rank matrix approximation, in the presence of missing data and outliers, has previously shown its significance as a theoretic foundation in a wide spectrum of tabulated information processing applications. To fit low rank models, minimizing the nuclear norm of matrices is a popular scheme, the computational load of which, however, is heavy. While bilinear factorization can largely mitigate the...
This paper investigates the distributed localization problem for sensor networks with noisy distance measurements. A distributed iterative algorithm called ECHO-MN is presented based on the signed barycentric coordinate representation, which can be calculated by relative distance measurements. The measurement noise model is presented followed by an unbiased distance estimator which utilizes the past...
Image data is frequently extremely large and oftentimes pixel values are occluded or observed with noise. Additionally, images can be related to each other, as in images of a particular individual. This method augments the recently proposed Generalized Low Rank Model (GLRM) framework with graph regularization, which flexibly models relationships between images. For example, relationships might include...
This paper presents the analysis and design of an adaptive parameter estimator for power electronics circuits. Adaptive parameter estimation has been demonstrated to be a useful technique for enabling novel controls, monitoring, and fault diagnosis techniques in power electronics systems. We present an analysis of factors that affect the performance, stability, and feasibility of a gradient-type parameter...
In this paper, we attack the estimation problem in Kalman filtering when the measurements are contaminated by outliers. We employ the Laplace distribution to model the underlying non-Gaussian measurement process. The maximum posterior estimation is solved by the majorization minimization (MM) approach. This yields an MM based robust filter, where the intractable ℓ1 norm problem is converted into an...
Aircraft scheduling is an important factor affecting the operating costs of airlines. Dispatching aircraft reasonably can not only maximize the benefits of the aircraft utilization, but also reduce flight delays. In this paper, we first transfer the scheduling model to the postman problem with the network model. Then, a scheduling model that use minimal aircrafts under the giving flight plan is put...
This paper proposes a diffusion proportionate affine projection sign algorithm for distributed estimation of sparse vector over network. The algorithm is derived by minimizing l1-norm intermediate error vector subject to a weighted constraint on the filter coefficients, where the positive definite weighting matrix is designed to accelerate the convergence of the nonzero coefficients for sparse vector...
In this paper, we present a localization approach that is based on a point-cloud matching method (normal distribution transform “NDT”) and road-marker matching based on the light detection and ranging intensity. Point-cloud map-based localization methods enable autonomous vehicles to accurately estimate their own positions. However, accurate localization and “matching error” estimations cannot be...
This paper proposes a robust tracking method with application to the DC-AC PWM converter of the green energy. The proposed method has the merits of hyperbolic tangential sliding hyperplane (HTSH), grey prediction (GP) and firefly algorithm (FA). The HTSH has the robustness of classical sliding mode control (SMC) and increases the system's convergence speed. However, once a highly nonlinear load occurs,...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.