A static control model is proposed based on wavelet transform weighted twin support vector regression (WTWTSVR). Firstly, new weighted matrix and coefficient vector are added into the objective functions of twin support vector regression (TSVR) to improve the performance of the algorithm. The performance test confirms the effectiveness of WTWTSVR. Secondly, the static control model is established based on WTWTSVR and 220 samples in real plant, which consists of prediction models, control models, regulating units, controller, and BOF. Finally, the results of proposed prediction models show that the prediction error bound with 0.005&#x25; in carbon content and 10&#xb0;C in temperature can achieve a hit rate of 92&#x25; and 96&#x25;, respectively. In addition, the double hit rate of 90&#x25; is the best result by comparing with four existing methods. The results of the proposed static control model indicate that the control error bound with 800 Nm3 in the oxygen blowing volume and 5.5 tons in the weight of auxiliary materials can achieve a hit rate of 90&#x25; and 88&#x25;, respectively. Therefore, the proposed model can provide a significant reference for real BOF applications, and also it can be extended to the prediction and control of other industry applications.

Chuang Gao

Minggang Shen

Xiaoping Liu

Lidong Wang

Maoxiang Chu

End-Point Static Control of Basic Oxygen Furnace (BOF) Steelmaking Based on Wavelet Transform Weighted Twin Support Vector Regression

The objective of this study is to propose a new operation method based on the universal grey number to overcome the shortcomings of typical interval operation in solving system fault trees. First, the failure probability ranges of the bottom events are described according to the conversion rules between the interval number and universal grey number. A more accurate system reliability calculation is then obtained based on the logical relationship between the AND gates and OR gates of a fault tree and universal grey number arithmetic. Then, considering an aircraft landing gear retraction system as an example, the failure probability range of the top event is obtained through universal grey operation. Next, the reliability of the aircraft landing gear retraction system is evaluated despite insufficient statistical information describing failures. The example demonstrates that the proposed method provides many advantages in resolving the system reliability problem despite poor information, yielding benefits for the function of the interval operation, and overcoming the drawback of solution interval enlargement under different orders of interval operation.

Feng Zhang

Shiwang Tan

Leilei Zhang

Yameng Wang

Yang Gao

Fault Tree Interval Analysis of Complex Systems Based on Universal Grey Operation

As the inertial navigation system cannot meet the precision requirements of global navigation in the special geographical environment of the Polar Regions, this paper presents Strapdown Inertial Navigation System (SINS)/Celestial Navigation System (CNS) integrated navigation system of airborne based on Grid Reference Frame (GRF) and the simulation is carried out. The result of simulation shows that the SINS/CNS integrated navigation system is superior to the single subsystem in precision and performance, which not only effectively inhibits the error caused by gyro drift but also corrects the navigation parameters of system without delay. Comparing the simulation in the middle and low latitudes and in the Polar Regions, the precision of SINS/CNS integrated navigation system is the same in the middle and low latitudes and in the Polar Regions.

Song Lijun

Zhao Wanliang

Cheng Yuxiang

Chen Xiaozhen

Based on Grid Reference Frame for SINS/CNS Integrated Navigation System in the Polar Regions

This paper focuses on the swing oscillation process of the synchronous generator rotors in a three-machine power system. With the help of bifurcation diagram, time history, phase portrait, Poincar&#xe9; section, and frequency spectrum, the complex dynamical behaviors and their evolution process are detected clearly in this power system with varying perturbation related parameters and different system parameters. Furthermore, combining the qualitative and quantitative characteristics of the chaotic motion, different paths leading to chaos coexisting in this system have been found. The Wolf method has been introduced to calculate the corresponding largest Lyapunov exponent, which is used to verify the occurrence of chaotic motion. These results obtained in this paper will contribute to a better understanding of nonlinear dynamic behaviors of synchronous generator rotors in a three-machine power system.

Xiaodong Wang

Caiqin Song

Analysis on Nonlinear Dynamic Characteristic of Synchronous Generator Rotor System

In this paper a Fractional PID Control is presented. This control was designed for a hydropower plant with six generation units working in an alternation scheme. The parameters and other features of such a set of hydrogeneration units have been used to perform the respective tuning up. In order to assess the behavior of this controlled system, a model of such nonlinear plant is regulated through a classical PID by classical linearization of its set points, and then a pseudo-derivative part is substituted into a Fractional PID. Both groups of signals contain variations of voltage suggesting some abrupt changes in the supply of electricity fed to the network. Both sets of resulting signals are compared; the simulations show that the Fractional PID has a faster response with respect to those plots obtained from the classical PID used.

O. A. Rosas-Jaimes

G. A. Munoz-Hernandez

G. Mino-Aguilar

J. Castaneda-Camacho

C. A. Gracios-Marin

Evaluating Fractional PID Control in a Nonlinear MIMO Model of a Hydroelectric Power Station

This paper proposes a time-delayed feedback control to improve collection performance of the multiple attractors wind-induced vibration energy harvester system. By employing a conversion mechanism for decoupling the electromechanical equations and the stochastic averaging method, the roles of the time-delayed feedback and the system parameters have been systematically examined. In the deterministic case, the time delay can control efficiently the birhythmic properties; thus one can realize a dividing line in the parameter plane that separates the space into two subspaces of generically distinct nature. Further, it is exclusively demonstrated that implementing time-delayed feedback control serves as a very simple but highly efficient scheme to increase the harvested energy from vibrations in presence of noise disturbances. Additionally, the time constant ratio and coupling coefficients can also be properly tuned to optimize power generation.

Qin Guo

Zhongkui Sun

Ying Zhang

Wei Xu

Time-Delayed Feedback Control in the Multiple Attractors Wind-Induced Vibration Energy Harvesting System

We introduce a new measure of complexity (called spectral complexity) for directed graphs. We start with splitting of the directed graph into its recurrent and nonrecurrent parts. We define the spectral complexity metric in terms of the spectrum of the recurrence matrix (associated with the reccurent part of the graph) and the Wasserstein distance. We show that the total complexity of the graph can then be defined in terms of the spectral complexity, complexities of individual components, and edge weights. The essential property of the spectral complexity metric is that it accounts for directed cycles in the graph. In engineered and software systems, such cycles give rise to subsystem interdependencies and increase risk for unintended consequences through positive feedback loops, instabilities, and infinite execution loops in software. In addition, we present a structural decomposition technique that identifies such cycles using a spectral technique. We show that this decomposition complements the well-known spectral decomposition analysis based on the Fiedler vector. We provide several examples of computation of spectral and total complexities, including the demonstration that the complexity increases monotonically with the average degree of a random graph. We also provide an example of spectral complexity computation for the architecture of a realistic fixed wing aircraft system.

Igor Mezi&#x107;

Vladimir A. Fonoberov

Maria Fonoberova

Tuhin Sahai

Spectral Complexity of Directed Graphs and Application to Structural Decomposition

Bike-sharing is a new low-carbon and environment-friendly mode of public transport based on the &#x201c;sharing economy&#x201d;. Since 2017, the bike-sharing market has boomed in China&#x2019;s major cities. Bikes equipped with GPS transmitters are docked along sidewalks that can be easily accessed through smartphone apps. However, this new form of transport has also led to problems, such as illegal parking, vandalism, and theft, each of which presents a major administrative challenge. Further, imbalances in user demand and bike availability need to be overcome to ensure a convenient, flexible service for customers. Hence, predicting a cyclist&#x2019;s destination could be of great importance to shared-bike operators. In this paper, we propose an innovative deep learning model to predict the most probable destination for each user. The model, called destination prediction network based on spatiotemporal data (DPNst), comprises three steps. First, the data is preprocessed and a pool of likely candidate destinations is generated based on frequent item mining. This candidate set is then used to build the DPNst model: a long short-term memory network learns the user&#x2019;s behavior; a convolutional neural network learns the spatial relationships between the origin and the candidate destinations; and a fully connected neural network learns the external features. In the final step, DPNst dynamically aggregates the output of the three neural networks based on the given data and generates the predictions. In a series of experiments on real-world stationless bike-sharing data, DPNst returned an F1 score of 42.71&#x25; and demonstrated better performance overall than the compared baselines.

Jian Jiang

Fei Lin

Jin Fan

Hang Lv

Jia Wu

A Destination Prediction Network Based on Spatiotemporal Data for Bike-Sharing

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Complexity publishes original research and review articles across a broad range of disciplines with the purpose of reporting important advances in the scientific study of complex systems.

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Chief Editor, Prof Sayama, is currently researching complex dynamical networks, human and social dynamics, artificial life, and interactive systems while working at Binghamton University, State University of New York.

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Complexity publishes original research and review articles across a broad range of disciplines with the purpose of reporting important advances in the scientific study of complex systems.

Complexity