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In order to obtain a driving force control strategy that can improve the overall performance of the longitudinal and lateral of the racing car, and at the same time can reconcile the contradictions between different strategies. In this paper, the possibility and advantages of coordination among multiple control strategies are first analyzed. Then, based on the dual-motor rear-wheel independent driving system, a longitudinal and lateral coordinated motion controller is designed, which consists of 4 parts: driving force estimator, ideal yaw rate generator, SMC-based yaw rate controller and SMC-based slip rate controller. Finally, the different target slip rate constraint conditions of the longitudinal motion and the lateral motion of the racing car are used to couple to realize the coordinated longitudinal and lateral motion control. Simulations and experiments show that the coordinated motion controllers can cooperate with each other and complement each other, and further improve the overall performance of the longitudinal and lateral motion of the car. In addition, the racing car that use coordinated motion controllers won 6 awards in FSEC, which were fully verified and recognized.

Effective integration and wide sharing of geospatial data is an important and basic premise to facilitate the research and applications of geographic information science. However, the semantic heterogeneity of geospatial data is a major problem that significantly hinders geospatial data integration and sharing. Ontologies are regarded as a promising way to solve semantic problems by providing a formalized representation of geographic entities and relationships between them in a manner understandable to machines. Thus, many efforts have been made to explore ontology-based geospatial data integration and sharing. However, there is a lack of a specialized ontology that would provide a unified description for geospatial data. In this paper, with a focus on the characteristics of geospatial data, we propose a unified framework for geospatial data ontology, denoted GeoDataOnt, to establish a semantic foundation for geospatial data integration and sharing. First, we provide a characteristics hierarchy of geospatial data. Next, we analyze the semantic problems for each characteristic of geospatial data. Subsequently, we propose the general framework of GeoDataOnt, targeting these problems according to the characteristics of geospatial data. GeoDataOnt is then divided into multiple modules, and we show a detailed design and implementation for each module. Key limitations and challenges of GeoDataOnt are identified, and broad applications of GeoDataOnt are discussed.

Surface meshes extracted from sparse medical images contain surface artifacts, there will produce serious distortion and generate numerous narrow triangle meshes. In order to eliminate the impact of the above factors, this paper presents a novel method for generating smooth and adaptive meshes from medical image datasets. Firstly, extracting the stack of contours by means of image segmentation and translating the contours into point clouds. The improved Multi-Level Partition of Unity (MPU) implicit functions are used to fit the point clouds for creating the implicit surface. Then, sampling implicit surface through dynamic particle systems based on Gaussian curvature, dense particles sampling in the high curvature region, sparse particles sampling in the low curvature region. Finally, generating triangle meshes based on particle distribution by using the Delaunay triangulation algorithm. Experimental results show that the proposed method can generate high-quality triangle meshes with distributed adaptively and have a nice gradation of triangle mesh density on the surface curvature.

Somatosensory control based on 3D sensors has been widely used as a virtual reality and motion capture technology in large-screen human–computer interactive systems. However, many issues still exist in human–computer interactive systems, such as inaccuracies of target tracking and poor anti-jamming performance. A federated tracking filtering algorithm is proposed in this paper to address these problems. The algorithm first pretreats the original data with dynamic adaptive filtering and an unscented Kalman filter and then applies a mean shift clustering algorithm on the preprocessed data. Experiments show that the correct tracking rate can reach 95.3% when the measured points are 200, while the correct tracking rate of mean shift algorithm is 90.7%. Furthermore, the noise points are found to be almost completely filtered by comparing the depth image before and after filtering. The federated tracking filtering algorithm is shown to guarantee accurate target tracking and excellent anti-jamming performance, and can significantly improve the interactive experience.

In this article, we concerned with the tracking control problem for a class of single-input single-output discrete switched nonlinear systems in the presence of uncertain parameters. We address a discrete-time sliding mode switching control scheme via disturbance compensator technique using saturation function and arbitrary switching method which is an effective robust way to reduce the chattering phenomenon and improve system control performance. The resulting closed-loop switched system is proved to be robustly stable such that the sliding mode surface of the closed control system is well obtained and the accuracy of the tracking error performance can be reached. Simulation results of the of electro-hydraulic servo system show that the presented sliding mode switching control scheme gives better tracking control performance over traditional sliding mode control scheme without disturbance compensator.

Linked Data is known as one of the best solutions for multisource and heterogeneous web data integration and discovery in this era of Big Data. However, data interlinking, which is the most valuable contribution of Linked Data, remains incomplete and inaccurate. This study proposes a multidimensional and quantitative interlinking approach for Linked Data in the geospatial domain. According to the characteristics and roles of geospatial data in data discovery, eight elementary data characteristics are adopted as data interlinking types. These elementary characteristics are further combined to form compound and overall data interlinking types. Each data interlinking type possesses one specific predicate to indicate the actual relationship of Linked Data and uses data similarity to represent the correlation degree quantitatively. Therefore, geospatial data interlinking can be expressed by a directed edge associated with a relation predicate and a similarity value. The approach transforms existing sim...

In order to solve the chattering problem of sliding mode controller, an intelligent terminal sliding mode control algorithm based on particle swarm optimization is proposed. The terminal sliding mode surface is used to ensure that the error converges within finite time on the sliding surface. The control law is divided into two parts, which are the equivalent control item and the auxiliary control item. The equivalent control item is calculated by the nominal model of the system, while the auxiliary control item is calculated by using the particle swarm optimization with adaptive weight. The appropriate performance index is designed to ensure that the sliding mode variable gradually converges to zero and eliminate the controller output chattering. Finally, the method proposed is applied to the control problem of inverted pendulum device. The results show the advantages of method proposed when compared to the traditional terminal sliding mode control with the same uncertainties.

In this paper, an impact time and angle constrained guidance (ITACG) is proposed based on the nonsingular terminal sliding mode control (NTSMC) theory. First, the guidance law is derived for stationary targets. The proposed ITACG consists of two parts. One part is designed for a missile to intercept a target from the desired impact angle and the other part aims to achieve the desired impact time. Two different terminal sliding mode surfaces are designed so that the missile can satisfy the impact time and angle constraints simultaneously. Corresponding to the designed sliding mode surfaces, two different Lyapunov candidate functions are proposed and analyzed, and stability conditions are obtained. Then, we extend the proposed guidance for constant acceleration targets. The time-to-go estimation method is modified based on the conception of predicted-intercept-point (PIP) with the constant acceleration targets and stability conditions are also revised. Compared with traditional sliding mode control (SMC) based ITACG, the proposed guidance law is a direct online method. It does not need to design the line-of-sight angle curve off-line, nor does it need to switch between impact time constrained guidance and impact angle constrained guidance. In the end, numerical simulation results show that the proposed impact time and angle constrained guidance law has a good performance even though the missile has a constant acceleration. Salvo attack of multi-missiles against one target is shown in the simulation part by applying the proposed guidance law.

Semantic heterogeneity of geospatial data is the main bottleneck for implementing linked data, intelligent recommendation and accurate discovery of data. The ontology theory is an effective way to solve the semantic heterogeneity of data. Morphological Characteristics is the important research content of Semantic heterogeneity of data. This paper mainly studies morphological characteristics of geospatial data, analyzes its concept, attribute, and relation, and puts forward its concepts system. On this basis, this paper builds the model of Morphology-Ontology of geospatial data and defines the method of formalization representation of morphological information. In the last part, this paper constructs Morphology-Ontology and applies it to the retrieval of metadata of the Data Sharing Infrastructure of Earth System Science. Verification tests show that Morphology-Ontology of geospatial data can solve the semantic heterogeneity of data effectively and improve the precision and recall of the result of data discovery significantly. The research methods and results of this paper are of great reference value to solve the semantic heterogeneity of data in other fields.

This paper addresses chaos suppression of the mechanical centrifugal flywheel governor system with output constraint and fully unknown parameters via adaptive dynamic surface control. To have a certain understanding of chaotic nature of the mechanical centrifugal flywheel governor system and subsequently design its controller, the useful tools like the phase diagrams and corresponding time histories are employed. By using tangent barrier Lyapunov function, a dynamic surface control scheme with neural network and tracking differentiator is developed to transform chaos oscillation into regular motion and the output constraint rule is not broken in whole process. Plugging second-order tracking differentiator into chaos controller tackles the “explosion of complexity” of backstepping and improves the accuracy in contrast with the first-order filter. Meanwhile, Chebyshev neural network with adaptive law whose input only depends on a subset of Chebyshev polynomials is derived to learn the behavior of unknown dynamics. The boundedness of all signals of the closed-loop system is verified in stability analysis. Finally, the results of numerical simulations illustrate effectiveness and exhibit the superior performance of the proposed scheme by comparing with the existing ADSC method.

In this paper, chaos control is proposed for the output- constrained system with uncertain control gain and time delay and is applied to the brushless DC motor. Using the dynamic surface technology, the controller overcomes the repetitive differentiation of backstepping and boundedness hypothesis of pre-determined control gain by incorporating radial basis function neural network and adaptive technology. The tangent barrier Lyapunov function is employed for time-delay chaotic system to prevent constraint violation. It is proved that the proposed control approach can guarantee asymptotically stable in the sense of uniformly ultimate boundedness without constraint violation. Finally, the effectiveness of the proposed approach is demonstrated on the brushless DC motor example.