Optimized state estimation for nonlinear dynamical networks subject to fading measurements and stochastic coupling strength: An event-triggered communication mechanism

summary:This paper is concerned with the design of event-based state estimation algorithm for nonlinear complex networks with fading measurements and stochastic coupling strength. The event-based communication protocol is employed to save energy and enhance the network transmission efficiency, where the changeable event-triggered threshold is adopted to adjust the data transmission frequency. The phenomenon of fading measurements is described by a series of random variables obeying certain probability distribution. The aim of the paper is to propose a new recursive event-based state estimation strategy such that, for the admissible linearization error, fading measurements and stochastic coupling strength, a minimum upper bound of estimation error covariance is given by designing the estimator gain. Furthermore, the monotonicity relationship between the trace of the upper bound of estimation error covariance and the fading probability is pointed out from the theoretical aspect. Finally, a simulation example is used to show the effectiveness of developed state estimation algorithm

A SLAM Algorithm Based on Adaptive Cubature Kalman Filter

We need to predict mathematical model of the system and a priori knowledge of the noise statistics when traditional simultaneous localization and mapping (SLAM) solutions are used. However, in many practical applications, prior statistics of the noise are unknown or time-varying, which will lead to large estimation errors or even cause divergence. In order to solve the above problem, an innovative cubature Kalman filter-based SLAM (CKF-SLAM) algorithm based on an adaptive cubature Kalman filter (ACKF) was established in this paper. The novel algorithm estimates the statistical parameters of the unknown system noise by introducing the Sage-Husa noise statistic estimator. Combining the advantages of the CKF-SLAM and the adaptive estimator, the new ACKF-SLAM algorithm can reduce the state estimated error significantly and improve the navigation accuracy of the SLAM system effectively. The performance of this new algorithm has been examined through numerical simulations in different scenarios. The results have shown that the position error can be effectively reduced with the new adaptive CKF-SLAM algorithm. Compared with other traditional SLAM methods, the accuracy of the nonlinear SLAM system is significantly improved. It verifies that the proposed ACKF-SLAM algorithm is valid and feasible

The Application of a Complex Composite Fractal Interpolation Algorithm in the Seabed Terrain Simulation

Seabed terrain modelling is one of the key technologies in the Subsea Environmental Information System, and this system is critical for underwater vehicle path planning. A composite fractal interpolation algorithm based on improved fractional Brownian motion (FBM) and an improved iterative function system (IFS) is proposed in this paper to increase the precision of the seabed terrain model for submarine topography and to account for the complexity and irregularity of fractal properties in each region. The MATLAB simulation experiment showed that fractal properties of the model built by the complex composite fractal interpolation algorithm were closer to real surface features. After calculation analysis, the model built by the complex composite fractal interpolation algorithm, when compared with the model built by the traditional interpolation algorithm or by the single fractal interpolation algorithm, had higher precision and was more suitable for path planning for underwater vehicles

A Novel Robust H∞ Filter Based on Krein Space Theory in the SINS/CNS Attitude Reference System

Owing to their numerous merits, such as compact, autonomous and independence, the strapdown inertial navigation system (SINS) and celestial navigation system (CNS) can be used in marine applications. What is more, due to the complementary navigation information obtained from two different kinds of sensors, the accuracy of the SINS/CNS integrated navigation system can be enhanced availably. Thus, the SINS/CNS system is widely used in the marine navigation field. However, the CNS is easily interfered with by the surroundings, which will lead to the output being discontinuous. Thus, the uncertainty problem caused by the lost measurement will reduce the system accuracy. In this paper, a robust H∞ filter based on the Krein space theory is proposed. The Krein space theory is introduced firstly, and then, the linear state and observation models of the SINS/CNS integrated navigation system are established reasonably. By taking the uncertainty problem into account, in this paper, a new robust H∞ filter is proposed to improve the robustness of the integrated system. At last, this new robust filter based on the Krein space theory is estimated by numerical simulations and actual experiments. Additionally, the simulation and experiment results and analysis show that the attitude errors can be reduced by utilizing the proposed robust filter effectively when the measurements are missing discontinuous. Compared to the traditional Kalman filter (KF) method, the accuracy of the SINS/CNS integrated system is improved, verifying the robustness and the availability of the proposed robust H∞ filter

Deployment Strategy for Charging Piles Based on Distribution Network Capacity Planning and Users’ Needs

Electric vehicles are the most potential transports in the future. However, the large scale of charging facilities will make a great influence on gird. There is a need to make a research on the construction of charging facilities. Based on the power demand characteristics of electric vehicle charging, distribution network capacity, charging system performance and other aspects, this paper mainly researched the deployment strategy of charging piles. First, the authors built up a model with characteristics of charging power demand of electric vehicle and a model of charging service system. The characteristic of daily load curve is analyzed. Second, based on these works, the authors designed the progress of strategy making. At last, the progress was verified by the actual use case

Deployment Strategy for Charging Piles Based on Distribution Network Capacity Planning and Users’ Needs

Electric vehicles are the most potential transports in the future. However, the large scale of charging facilities will make a great influence on gird. There is a need to make a research on the construction of charging facilities. Based on the power demand characteristics of electric vehicle charging, distribution network capacity, charging system performance and other aspects, this paper mainly researched the deployment strategy of charging piles. First, the authors built up a model with characteristics of charging power demand of electric vehicle and a model of charging service system. The characteristic of daily load curve is analyzed. Second, based on these works, the authors designed the progress of strategy making. At last, the progress was verified by the actual use case

Measurement and spatio-temporal heterogeneity analysis of the coupling coordinated development among the digital economy, technological innovation and ecological environment

In-depth exploration of the coupled and coordinated relationship among regional digital economy (DE), technological innovation (TI) and ecological environment (EE) is a vivid embodiment of implementing sustainable development. In order to show the spatiotemporal features of the coupling coordination degree (CCD) from 2011 to 2020, this study builds an evaluation index system from three target levels, namely, the digital economy DE, science and technology innovation TE, and ecological environment EE. Based on this, global and local spatial econometric models, namely the global Moran's I index and the spatio-temporal geographically weighted regression (GTWR) model, are used to identify the spatio-temporal heterogeneity features of each explanatory variable on the CCD. The study results include: (1) The comprehensive evaluation index shows a rising trend, but the development is uneven among systems. (2) The CCD continues to rise steadily, and the regional disparity is widening; the transformation from the near-disorder level to the primary coordination level is realized over the research period. Spatially, the coupling coordination is higher in the eastern and southern regions, while the western and northern regions are relatively low. (3) The GTWR model demonstrates that human capital, urbanization rate, and openness to the outside world promote the CCD. In contrast, the social unemployment rate inhibits CCD, among which human capital is the main force behind coupled and coordinated development