Narrow Results

As a new cross-discipline, the complexity science has penetrated into every field of economy and society. With the arrival of big data, the research of the complexity science has reached its summit again. In recent years, it offers a new perspective for traffic control by using complex networks theory. The interaction course of various kinds of information in traffic system forms a huge complex system. A new mesoscopic traffic flow model is improved with variable speed limit (VSL), and the simulation process is designed, which is based on the complex networks theory combined with the proposed model. This paper studies effect of VSL on the dynamic traffic flow, and then analyzes the optimal control strategy of VSL in different network topologies. The conclusion of this research is meaningful to put forward some reasonable transportation plan and develop effective traffic management and control measures to help the department of traffic management.

To explore the rumor propagation dynamics in online social networks (OSNs) and propose the corresponding control strategies, a novel Ignorants-Spreaders-1-Spreaders-2-Removers (I2SR) rumor-spreading model with general incidence is first formulated in heterogeneous networks. This model covers the bilinear incidence and nonlinear incidence, and considers the time delay in the rumor-spreading process, which is universal and practical. We analytically derive the basic reproduction numbers, which determine the existence of rumor-spreading equilibria but also the global dynamics of the model. Moreover, the Lyapunov–LaSalle principle and the graph-theoretic approach prove the global asymptotic stability of the rumor-free/rumor-spreading equilibria in detail. Significantly, the effects of various strategies, including uniform control, targeted control, and acquaintance control, are implemented and compared. Finally, the developed theoretical results are tested via numerical simulations and a real case data of rumors, showing that the model can more accurately simulate rumor-spreading in OSNs.

Robot arm positioning is an important factor in the robotic process. However, the robot manipulator experiences positioning inaccuracies. This positioning error is due to the dynamic inefficiencies of its actuator: DC servomotor. In a bid to resolve this actuator problem, an electro-rheological (ER) clutch-brake mechanism is employed. This clutch-brake mechanism can actuate and halt the motion of the robot arm. This rotary mechanism consists of two similar clutches that are driven to rotate in the opposite directions and an individual ER brake that provides braking torques to halt the manipulator at the required positions. The main aim of this paper is to establish a control strategy for the ER actuated robot arm by means of model validation with the experimental results. This study is conducted to understand the ER robotic positioning control for future applications.

Lighting energy consumption occupies a large proportion in the building electricity consumption. It cannot only save energy, but also reduce the uneven and constant illumination of the working face, which makes full use of the natural lighting and combines with the intelligent lighting control. An office building in Zhengzhou of China has been selected as an example for analyzing the climatic factors that influence building daylighting and the factors of the building itself, the illuminance of working faces in different sky models and at different times has been simulated and calculated to analyze the illuminance variation law in the direction of room depth and parallel direction of side Windows. Partition and point combined constant illumination control strategy for the lamps in different areas has been put forward and realized by BP neural network algorithm. By controlling the dimming of artificial light source and adjusting the curtain opening degree intelligently, uniform and constant illumination has been achieved. Energy saving effect in combination with natural lighting has been evaluated to prove that the control strategy cannot only maintain constant illumination in every working face but also significantly reduce the electric energy consumption and carbon dioxide emissions.

With the rapid development of unmanned aerial vehicle (UAV) technology, UAV has been widely used in agricultural plant protection, electric power inspection, security patrols, and other fields. However, the control system of the UAV is a complex human–computer interaction system, which requires higher requirements in practical applications. Due to differences in hardware design, software development, and other aspects among different manufacturers, these UAV control systems require high hardware requirements, resulting in a long development cycle. At the same time, in practical applications, due to various reasons, there are equipment failures that are difficult to detect and eliminate in a timely manner. This paper used the UAV graphical control strategy identification method based on cloud server technology, and used the support vector machine (SVM) algorithm to analyze its identification accuracy. The research results showed that when other conditions were the same, the number of researchers and experts who were satisfied with the drone trial effect of the cloud server was 42 and 10, respectively, accounting for 84% and 100%. It indicates that they believe that the cloud server can effectively improve the effectiveness of the drone graphical control strategy recognition method, indicating a positive relationship between the two.

Plug-in hybrid electric vehicles (PHEVs) have been offered as alternatives that could greatly reduce fuel consumption relative to conventional vehicles. A successful PHEV design requires not only optimal component sizes but also proper control strategy. In this paper, a global optimization method, called parallel chaos optimization algorithm (PCOA), is used to optimize simultaneously the PHEV component sizes and control strategy. In order to minimize the cost, energy consumption (EC), and emissions, a multiobjective nonlinear optimization problem is formulated and recast as a single objective optimization problem by weighted aggregation. The driving performance requirements of the PHEV are considered as the constraints. In addition, to evaluate the objective function, the optimization process is performed over three typical driving cycles including Urban Dynamometer Driving Schedule (UDDS), Highway Fuel Economy Test (HWFET), and New European Driving Cycle (NEDC). The simulation results show the effectiveness of the proposed approach for reducing the fuel cost, EC and emissions while ensuring that the vehicle performance has not been sacrificed.

In this paper, we aim to propose a new chemostat model with continuous microbial culture and harvest, and to investigate the dynamics of the model. Different to the conventional ones, our model includes a constant periodic flocculant transmission. For the proposed system, by using theory of impulsive differential equations, we show that the microbe-extinction periodic solution is globally asymptotically stable when a threshold value is less than 1, and system is permanent when a certain threshold value is greater than 1. Then, according to the threshold associated with microbial extinction or existence, the control strategy for microbial continuous cultivation and harvest is discussed. Under such control strategy, continuous microbial culture and harvest can be achieved by adjusting input time, input amount or concentration of the flocculant. Finally, an example with numerical simulations is given to illustrate our theoretical conclusions.

We propose and analyze a TB transmission model with nonlinear incidence rate, immunization and medical treatment. First, the existences and stabilities of the equilibrium are studied. The results indicate the basic reproduction number ${\Re }_0$ is the threshold of disease extinction and persistence. The disease-free equilibrium is globally asymptotically stable when ${\Re }_0<1$, and the disease will gradually disappear. The unique positive equilibrium is local stability and the disease is uniformly persistent when ${\Re }_0>1$. Second, optimal control is added to the original model because of limited resources. Finally, the stability of the equilibrium and the theoretical results of optimal control are verified by numerical simulations, and the sensitivity of the parameters is analyzed by the PRCC method.

In this paper, a mathematical model of Ebola virus with contact tracing as a control strategy was developed and analyzed. We considered the model without contact tracing and with perfect contact tracing. The two sub-models have been explicitly analyzed. In the first sub-model, it has been found that the disease-free equilibrium (DFE) is both locally and globally asymptotically stable whenever the associated control reproduction number is less than one. The endemic equilibrium point (EEP) is globally asymptotically stable whenever the associated control reproduction number is greater than one. In the second sub-model, it has been found that the DFE is both locally and globally asymptotically stable whenever the control reproduction number is less than one. The EEP is globally asymptotically stable whenever the control reproduction number is greater than one. The full model has also been analyzed, which shows that the DFE is both locally and globally asymptotically stable whenever the associated control reproduction number is less than one. The EEP is globally asymptotically stable whenever the control reproduction number is greater than one. In sensitivity analysis part, effective contact rate for humans was very sensitive in increasing the basic reproduction number and personal hygiene was very sensitive in decreasing the basic reproduction number also, numerical simulation shows that the Ebola virus can be wiped out in society if contact tracing and personal hygiene can be implemented perfectly in the human population.

In this paper, a new artificial detrusor system is proposed to achieve continuous control over the urination process and realize the normal voiding process of human (NVPH). The system is powered by a wireless power transfer (WPT) module, controlled by a control module and actuated by a shape memory alloy (SMA) spring. The design method of the SMA springs is proposed. Two control strategies are proposed to achieve NVPH. The first strategy is an open-loop control strategy based on the result of finite element analysis (FEM) simulation results and calculation of the derived system governing equations. The second strategy is a closed-loop control strategy based on the collection of feedback data and algorithmic processing. Both strategies are verified by experiments. The results show that the proposed system is feasible and both strategies can achieve NVPH. It can provide reference and guidance for the design of artificial detrusor system and formulation of control strategies.

The controlling of complex networks is one of the most challenging problems in modern network science. Accordingly, the required energy cost of control is a fundamental and significant problem. In this paper, we present the theoretical analysis and numerical simulations to study the controllability of complex networks from the energy perspective. First, by combining theoretical derivation and numerical simulations, we obtain lower bounds of the maximal and minimal energy costs for an arbitrary normal network, which are related to the eigenvalues of the state transition matrix. Second, we deduce that controlling unstable normal networks is easier than controlling stable normal networks with the same size. Third, we demonstrate a tradeoff between the control energy and the average degree (or the maximum degree) of an arbitrary undirected network. Fourth, numerical simulations show that the energy cost is negatively correlated with the degree of nodes. Moreover, the combinations of control nodes with the greater sum of degree need less energy to implement complete control. Finally, we propose a multi-objective optimization model to obtain the control strategy, which not only ensures the fewer control nodes but also guarantees the less energy cost of control.

Granting those heart failure patients who are recipients of an implantable rotary blood pump (iRBP) greater functionality in daily activities is a key long-term strategy currently being pursued by many research groups. A reliable technique for noninvasive detection of the various pumping states, most notably that of ventricular collapse or suction, is an essential component of this strategy. Presented in this study is such a technique, whereby various indicators are derived from the noninvasive pump feedback signals, and a suitable computational methodology developed to classify the pumping states of interest. Clinical telemetry data from ten implant recipients was categorized (with the aid of trans-oesophageal echocardiography) into the normal and suction states. These data are used to develop a pumping state classifier based on an artificial neural network (ANN). Nine indices, derived from the noninvasive impeller speed signal, form the inputs to this ANN classifier. During validation, the resulting ANN classifier achieved a maximum sensitivity of 98.54% (609/618 samples of 5 s in length) and specificity of 99.26% (12,123/12,213 samples) for correct detection of the suction state. The ability to detect the suction state with such a high degree of accuracy provides a critical parameter both for control strategy development, and for clinical care of the implant recipient.

A compartmental model is established for schistosomiasis infection in Qianzhou and Zimuzhou, two islets in the center of Yangtzi River near Nanjing, P. R. China. The model consists of five differential equations about the susceptible and infected subpopulations of mammalian Rattus norvegicus and Oncomelania snails. We calculate the basic reproductive number R₀ and discuss the global stability of the disease free equilibrium and the unique endemic equilibrium when it exists. The dynamics of the model can be characterized in terms of the basic reproductive number. The parameters in the model are estimated based on the data from the field study of the Nanjing Institute of Parasitic Diseases. Our analysis shows that in a natural isolated area where schistosomiasis is endemic, killing snails is more effective than killing Rattus norvegicus for the control of schistosomiasis.

The sterile insect technique (SIT) has been applied as an alternative method to reduce or eradicate mosquito-borne diseases. To explore the impact of the sterile mosquitoes on controlling the wild mosquito populations, in this paper, we further extend the work in [J. Li, New revised simple models for interactive wild and sterile mosquito populations and their dynamics, J. Biol. Dyn. 11(S2) (2017) 316–333] and formulate delayed models for interactive wild and sterile mosquitoes, which can depict wild mosquito population undergoing distinct stages of development during a lifetime. By performing mathematical analysis, the threshold dynamics of the proposed models are explored, respectively. In particular, Hopf bifurcation phenomena are observed as the delay $\tau$ is varying. Numerical examples illustrate our findings.

A dynamic model of a combined radiant floor heating (RFH) and domestic hot water supply (DHWS) system is developed and validated by using measured data gathered from an experimental test facility. The validated model was used to study the dynamic responses of the system under different operating conditions. Optimal control and predictive control strategies were designed and simulated to study system performance and energy consumption. Results showed that the control strategy with the heating load prediction could save up to 12.7% energy. Also, the optimal control strategy with optimal set-points could save 8.6% energy input to the boiler and 42.9% pump energy consumption while maintaining the zone temperatures and DHWS temperatures close to their respective set-points.

Control strategies are the chief attraction in the field of rehabilitation engineering, and especially in a functional electrical stimulation (FES) system, a reliable control method is important for paralyzed patients to restore lost their functions. In this paper, we have presented a demonstration of the control strategy, which is based on the patient-driven loop, used in a non-invasive FES system for hand function restoration. With the patient-driven loop control, hemiplegic patients could use their residual capabilities, such as shoulder movements in their sound extremities, the myoelectric signals generated from different muscles, etc, to operate the FES system. Here we have chosen the most common and acceptable signals as the input sources, i.e. electromyographic (EMG) signals, to control a non-invasive FES system, generating the electrical stimuli to excite the paralyzed muscles. In addition, EMG signals recorded by the sensors in the electrical stimulator can serve both as the trigger of the system and as the adjustment of the electrical stimulation parameters, thereby improving the system's performance and reliability. From the experimental results, subjects can successfully use their residual capabilities to control the FES system and restore their lost hand functions as well. On the other hand, from the viewpoints of rehabilitation and psychology, hemiplegics will benefit greatly by using their residual capabilities to regain their lost functions. It is believed that the patient-driven loop control is very useful, not only for the FES system in this study, but also for other assistive devices. By the control strategy proposed in this paper, we deeply hope that patients will benefit greatly and regain their self-confidence.

Along with the applications of distributed resources (DR), nonlinear power electronic devices and nonlinear and unbalanced loads, some deteriorative influences have been caused such as poor power quality and stability issues. The Static Synchronous compensator (STATCOM), as one of newest reactive power compensations with the best performances, plays an important role in the power system up to now. This paper deals with the fundamental compensation principle, the main circuit, current detection method, control strategy and application prospect of STATCOM which can reduce the line loss of power grid and the power loss of asynchronous motor.

This paper found the deficiency of classical Z-N method in optimization of PID parameters, proposed the intelligent optimization algorithm of PID parameters. The stimulation and experiment showed that the PID parameters getting from this algorithm are efficient, accurate and speedy. This paper used algorithm for hydraulic control system of jumbolter. The stimulation and experiment showed that when peak oil pressure of relief chamber is changed, optimum algorithm will find suitable and based on MAX power requirement to change displacement of relief surface, which lead to changing displacement of impact piston, at the same time, it will change the impact power and frequency of impactor, and realize impactor auto change working parameters based on the different situation under suitable parameters and MAX power working condition. The experiments show that it has a certain reference value for other control objects and control process.

In recent years, micro grid system has received more and more attention internationally. As the most effective form of distributed generations, micro grid system has found wide applications in many areas. Micro grids are low voltage (LV) distribution networks comprising various distributed generators (DGs), storage devices, and controllable loads that can operate either interconnected or isolated from the main distribution grid as a controlled entity. This paper describes the operation of a central controller for micro grids. Different control methods of micro grid system and their advantages and shortcomings are carried out and analyzed. The controller aims to optimize the operation of the micro grid during interconnected operation, that is, maximize its value by optimizing the production of the local DGs and power exchanges with the main distribution grid. Two market policies are assumed including demand side bidding options for controllable loads. The developed optimization of a typical LV case study network operating under various market policies and assuming realistic spot market prices and DG bids reflecting realistic operational costs. A laboratory scale micro grid system is proposed as an example to verify the micro grid control strategy. The operation experimental results show that the laboratory scale micro grid system can operate in gridconnected or islanded mode, with a seamless transfer from one mode to the other, and hence increase the reliability of energy supplies.

Research for sail-assisted technologies should be strengthened for promoting the development of sail assisted project. This paper mainly investigates the sail structure design, dynamic performance and the sail driving control strategy for the large ocean-going sail-assisted ship. For the circular thin optimal sail of one 48000 DWT bulk carrier, the aerodynamic characteristics was analyzed and the sail area was selected through combining with the model parameters from the results of the experimental analysis. Then, the torque for each set of sail was roughly calculated. According to the actual requirements of the sail driving control for energy-saving and driving-safety the hydraulic control is feasible. Compared two traditional hydraulic control systems, the improvement scheme of hydraulic control with variable-frequency technology was further proposed which is a more optimal control method for sail driving control of large ocean-going ships.