Earticle

Temperature is a universe and significant data in production and scientific experiment, effective measurement and control of the temperature are widely applied in every part of national economy. Therefore, temperature control has great significance; relevant requirements regarding temperature control are also higher and higher. Temperature command system for animal house is a complex system with features of time varying, nonlinear, inaccurate model and unknown operating circumstance, temperature controlled by air-conditioner is less accurate and will affect the stability of the system performance. Regarding existing problems of long responding time, less stability and other disadvantages of the conventional PID control, we hereby raise a new approach of variable universe fuzzy PID control which is characterized with quick responding speed, better stability and stronger anti-interruption performance. Through the application of variable universe fuzzy control theory, which combined with the advantages of conventional PID and variable universe fuzzy control, forming the calculation of self-applied variable universe fuzzy control PID. Improve the accuracy of fuzzy inference by variable universe control theory, and realize the online tuning of PID data through fuzzy inference. Stimulate on Matlab, relevant stimulation results revealed that the control ways is clearly superior than conventional PID control, therefore effectively improve the dynamic property, stability precision and robustness, the system has better future of industrial application.

Given a site set P and an object set R, Bichroamtic RkNN query of site q∈P finds objects that take q as k nearest neighbors, which can been used to evaluate the influence of q on objects. Existing methods execute RkNN query by pruning strategies based on spatial indexes. For any change of object datasets (like moving objects), these methods need to compute RkNN again. The paper proposes a new algorithm based on K-order Voronoi diagrams. For a fixed site q, its RkNN region does not change whatever object datasets are updated or not. So we only search objects in Voronoi region of q. In this paper, we first give some propositions that provide the searching bounds. Then, BRKVD algorithm is proposed for RkNN query based on R-Tree, which supports the frequent changes of datasets and k. The experimental results show that the proposed algorithm performs the existing algorithms on efficiency.

This paper presents the dynamic model and control strategy of active power filter (APF) on dq0-frame in three-phase four-wire system. The structure of the APF is the three-leg split-capacitor. The dq0-frame with Fourier (DQF) method is used to calculate the reference currents on dq0-frame. The pulse width modulation (PWM) with PI controllers is considered in the paper. Moreover, the principle of the PI controller design for three current loops and two voltage loops are completely presented. The discrete design approach is used to design all controllers in the system. In addition, the hardware in the loop (HIL) technique is applied to simulate the harmonic elimination using the APF in the paper. The results show that the control strategy and the design approach presented in the paper can provide the good performance of the APF. Furthermore, the source currents after compensation can also follow the IEEE Std.519-1992 and IEEE Std.1459-2010.

In this paper, we argue that total three desirable properties should be satisfied so that a function to be learned or interpolated from a set of input-output examples can cross all the given examples with minimal oscillations among the examples. As long as the number of given examples exceeds the dimension of example and meanwhile none existing hyper-plane, in real vector space of example’s dimension, passes through all the given examples exactly, we can construct one simple function learning solution, which is expressed as a sum of two terms: one is an example-influence term that consists of the outputs of a number of basis functions and another is a linear term, to allow all the three desirable properties to be satisfied exactly. Experiments show that the solution can simulate both continuous and discontinuous functions even with very sparse given examples.

Sensor networks have a significant potential in diverse applications, and some have already been deployed in monitoring system of living environment. With the increasing complexity of application logic, difficulties in monitoring sensor networks have become a barrier to the adoption of these networks. The difficulties are due not only to their inherently distributed nature but also to the need for mechanisms to address their harsh operating conditions such as unreliable communications, faulty nodes, and extremely constrained resources. Living Environment monitoring is composed mainly of sensor data on air, water, and ecotourism quality. Wireless sensor networks(WSNs) entail a substantial loss of energy because there is a need for some mechanisms that can select multiple communications in single communications. This kind of merging is called data aggregation. This paper presents a secure and authentication-based approach to the data aggregation of living environment. User authentication is performed using a secure hash algorithm. This paper also introduces a neural network to check bad packet communications over the network. The results indicate that the proposed approach is more reliable and efficient than existing ones.

Thin-walled components have characteristics of high intensity and light mass and are used widely in aeronautical industry. NC milling is one of the most popular machining methods for the thin-walled components. Because of their poor rigidity, the deformation of the thin-walled workpieces caused by cutting force is a main factor that decreases the machining precision and increases aeronautical product cost. Based on the analyses of the machining deformation mechanism and basic machining deformation characteristics of the thin-walled workpieces, a NC milling deformation forecasting approach is presented based on CAD/CAM/FEA integration to forecast the machining deformation of the aeronautical thin-walled workpieces. Taking a typical workpiece for example, the proposed deformation forecast framework is validated by the analytic and experimental results. The straight side walls of aluminum LY12CZ workpieces are processed on a vertical machining center THA5656 and their errors are analyzed. Based on orthogonal tests, the deformation characters of the thin-walled workpieces are discussed under different cutting conditions. By the comparison of experimental results and FEA results, although there exist definite difference, their variation tendencies are similar on the whole. Thus, the FEA model is validated. The research can provide support for machining deformation control and machining simulation model verification.

To solve the slow convergence speed, low precision in later period and tedious parameter setting of differential evolution when applied to complex optimization functions, an improved differential evolution algorithm (dn-DADE) based on dynamic adaptive strategy is proposed. Firstly, the elite solutions of current population are utilized in the new mutation strategy (DE/current-to-dnbest/1) to guide the search direction, and then these optional elite solutions tend to the global optimal solution in the late stage of evolution to balance the diversity of population and convergence speed. Secondly, the adaptive update strategies of scaling factor and crossover factor are designed for control parameter values self-adapting at different search stages, thus improve the stability and robustness of the algorithm. A set of 14 benchmark functions is adopted to test the performance of the proposed algorithm. The results show that dn-DADE algorithm has the advantages of remarkable optimizing ability, higher search precision, faster convergence speed and outperforms several state-of-the-art improved differential evolution algorithms in terms of the main performance indexes.

In the location estimation technology using WLAN, RSSI coming from each AP has a large deviation due to complicated and varying indoor environments. Especially when a laptop is used for work inside a building or when a location-based service is required, the AP needs to be changed depending on RSSI coming from the laptop or the type of work. However, most studies are about hand-over technology between different types of devices based on mobile devices with good portability. Hand-over technology is generally controlled and managed at the server to identify the AP information and select a network quickly. Though this is the best choice to select network and connect communication quickly, any mobile device that is not registered in the server cannot be provided with the service. The current paper proposes a network selection algorithm at the starting point of mobile device as a way to solve the problem through simulation and performance evaluation.

For the vertical and horizontal dual 5-axis system of a new turning-milling compound machining center, the dedicated post processor for 5-axis is developed by C++ programming language, B-axis pendulum angle error measurement technology and nonlinear error compensation algorithm are studied; and also analyzed and verified in actual processing; Researches show that: the dual 5-axis post processor works correctly and efficiently, better processing accuracy than 0.05mm can be obtained by nonlinear interpolation compensation for B-axis pendulum angle for 3 times, which meets the demand of crafts machining.

Special fork is an important load-bearing component in the transmission structure, requiring relatively high abrasion resistance and impact toughness. The fork usually works under the conditions of impact and abrasion and the effect of alternating load, therefore it is prone to fatigue damage. The reliability of the fork could exert direct influence on the stability and safety of the vehicles. By highlighting the fact that the shifting special fork in the transmission of some type of light vehicle is suddenly broken and become invalid during the vehicle driving process, this article had made static strength analysis and fatigue lifetime expectation research from the perspectives of Finite Element Method and accumulated damage. The findings of the analysis will provide reference for the improvement of components structure, finding of the root cause of the accidents as well as the selection of the general design mechanism.

In this paper, synchronization of chaotic and Lu system has been done using the active sliding mode control strategy. Regarding the synchronization task as a control problem, fractional order mathematics is used to express the system and active sliding mode for synchronization. It has been shown that not only is the performance of the proposed method satisfying with an acceptable level of control signal, but also a rather simple stability analysis is performed. The latter is usually a complicated task for nonlinear chaotic systems

This paper investigates the chaos control problem for Lorenz-Stenflo chaotic system with uncertain parameters. Based on the interval matrix theory, the Takagi-Sugeno(T-S)fuzzy model is applied to the Lorenz-Stenflo chaotic system with uncertain parameters.Based on theLyapunov stability theorem, the sufficient stabilitycondition for the Lorenz-Stenflo chaotic system is presented as a set of linear matrix inequality (LMI) forthe first time and the strict mathematical norms of LMI are given. Then the controller feedback gain can be obtained by solving a set of linear matrix inequality. Finally, simulation results for the Lorenz-Stenflo chaotic system are provided to illustrate the effectiveness of the proposed scheme.

The standard Glowworm Swarm Optimization(GSO) has poor global search ability and easily trap into local optimum. In order to solve these problems, a Quantum Glowworm Swarm Optimization Algorithm based on Chaotic Sequence(QCSGSO) is proposed in this paper.Firstly, chaotic sequence is generated to initialize the population, which has higher probability to cover more local optimal areas, and provides a good condition for further optimization and tuning.Then, quantum behavior is applied to elite population, which makes individuals locate in any position of the solution space randomly with a certain probability, greatly enhances the algorithm’s capability of global searching and local optimum jumping. Finally, QCSGSO adopts single dimension loop swimming rather than the original fixed step movement mode, which not only improves the solution precision and convergence speed, but also solves GSO’s problem about too sensitive to the step-size, and enhances the robustness of the algorithm indirectly. The results of simulation experiments show that the proposed method is feasible and effective.

This paper presents an implementation of trajectory planning method while considering velocity constraints for a two-wheeled mobile robot (TMR) on Xenomai. A Bezier curve is utilized to make a smooth path. A convolution operator was used to generate a velocity profile for the travel distance of the planned path while also giving consideration of the velocity constraints of the TMR. The trajectory planning are performed on Xenomai with multitasking structure, which is a real-time Linux system developed by open-source projects. Finally, the periodicity and schedulability of real-time tasks and trajectory tracking performance were analyzed. Moreover, the efficiency of real-time operating system was also examined.

For controlling the deployment of subsatellite, the dumbbell model of tethered satellite system (TSS) is built. The paper develops a nonlinear receding horizon feedback control rule based on the nonlinear dynamics model using an indirect Legendre psuedospectral method. The nonlinear control problem is approximated with successive linear problems obtained via a quasilinearisation around reference trajectory. The feedback gains of receding horizon control could be obtained via solving a two-point boundary value problem which may be discretized into a set of linear algebraic equations by the indirect Legendre pseudospectral method. A numerical example is included to demonstrate the strong stability and high accuracy of the feedback controller under initial perturbations.

Urban expressway plays an important role in the urban road network. It is gradually shifting from large-scale infrastructure-oriented to refinement of traffic management. In order to improve the efficiency and safety of urban expressway, macroscopic dynamic traffic flow model is extended under speed guidance control. Multi-objective optimization model is established based on the total travel time of vehicles and the value of speed guidance changes. Three scenarios are carried out with Strength Pareto Evolutionary Algorithm. The optimal scenario is adopted based on set theory then the best solution is determined. Simulation analysis is carried out in simulation platform under the optimal solution. The results show that speed guidance control has a good effect to smooth traffic flow, alleviate traffic congestion and improve traffic safety which can be applied in practice to provide a theoretical support for active traffic management.

In this paper a method that allows for the control of a humanoid robot with foot sensors through an imitation control approach is presented. Our approach does not use any prior analytical or mathematical robot modeling (e.g. forward or inverse kinematics). The key concept is to trace the CoP (center of pressure) as fast as possible and to control the ankle of the robot’s support foot prior to impact. The experimental results demonstrate that a humanoid robot can successfully imitate the motions of the operator and can walk stably by utilizing both the CoP and controlling the robot’s ankle.

Urban water supply schemes are studied with multi-attribute characteristics taken into consideration. This paper proposes an optimized urban water supply scheme based on grey system theory. In the model, optimized indicators are given and their weights are acquired through optimized grey related analysis. These indicators are subject to standardization and are calculated to get grey incidence degree. The optimal water supply scheme is determined by the grey incidence degree. Finally, empirical test on the water supply scheme of a city is conducted to prove its objectivity, feasibility and reliability.

Through researching the traffic flow regularity of single intersection, this paper puts forward an intelligent traffic light (design) method based on BP neutral network principle and fuzzy control theory, in which the variable parameter is the dynamic change of traffic flow. The traffic light control system based on the neutral network fuzzy control technology breaks through the traditional mechanical timing pattern and general control mode. According to the real-time traffic flow, this technology can operate flexibly, and it has “Associative Memory” function when it realizes the fuzzy inference by neutral network .Thus it can meet the emergency of single transformation under any circumstance and then reach the optimum delay time of green light. The simulation result by MATLAB shows that the neutral network fuzzy control technology is superior to general fuzzy control method, which greatly improves the traffic utilization and brings the obvious economic benefit.

In this paper we derive a state variable estimation method of discrete stochastic dynamical systems. It aims to obtain accurate estimation with short computing time. Therefore, the point of this paper is to discuss a construction of Kalman filter algorithm on the reduced model. First, we construct a reduced model by using balanced truncation method. Further, we apply state variable estimation steps of discrete stochastic dynamical systems by using Kalman filter on the reduced model. Thus, Kalman filter algorithm will be constructed on the reduced model.

Auto-disturbance-rejection control (ADRC) technology is nonlinear robust control technology. Its nonlinear feedback relies on the size and direction of the error between desired and the actual trajectory. When the controlled object is disturbed by uncertain factor or its parameters change, ADRC can transform nonlinear system into an integral series structure of linear system by using nonlinear transformation, what can realize feedback linearization of dynamic system and improve system’s control performance. According to above, we propose to apply ADRC technology to brushless DC motor control system to restrain torque ripple and improve system’s disturbance-rejection in this paper. After theoretical analysis the feasibility of this method, we made a simulation. Simulation results show that the effects of torque ripple suppression and anti disturbance ability of the system have been improved.

The direct current motor is one of the first machines devised to convert electrical power into mechanical power, and its origins can be traced to the disc-type machines conceived and tested by Michael Faraday. Its primary goal is to design a digital Proportional-Integral-Derivative (or PID) controller in a PLD’s devices environment to control the speed of DC motor system. This paper attempts to address two major problems by means of a PID controller. The first problem was system non-linearity that arose due to the nature of the hardware. The second problem was system unreliability when the DC motor load was varied.

High-speed railway subgrade settlement forecasting is an important part to ensure ride comfort and stability of the high-speed railway line. Based on the measured settlement data of Lan-Xin Railway DK649+500D-K650+000 section, three kinds of single forecast methods, including Hyperbolic method, Three-point method and Asaoka method are adopted for the high-speed railway subgrade settlement forecasting. The least squares support vector machine in adopted for its unique advantages in solving small sample data and nonlinear data. Combination forecast model is established by setting different weights of the single forecast methods. Simulation results show that the systematic errors in the Combination forecast model are less than that in the single forecast methods. Compared with the single forecast methods, the Combination forecast model has higher forecasting accuracy and better applicability.

Aiming at the problem of long cycle and high cost in designing power valve products at present, a nuclear power valve design method for collaborative design, simulation and optimization is put forward. Through the summarized characteristics of nuclear power valve products in CAE series, the basic framework of parametric CAE analysis is constructed. Combined with parametric variant design and simplification module for valve parts, the heterogeneous information between CAD and FEA of valve models is expressed by using the universal data exchange technology. According to the integrated development framework, an integrated system, which integrates parametric design, multi-characteristic simulation, and multidisciplinary design optimization for the nuclear power valves together supporting heterogeneous model transfer, is constructed and validated through a case. Through integration of heterogeneous CAD/CAE software such as UG, ANSYS and iSIGHT, the analytical efficiency is enhanced by coupling respective and unique advantage of various software systems. This transfer is benefit for mutual coordination and information sharing that improves the automation in design and analysis on the valve products.

This paper is to develop an empirical model of information system to improve performance ability in patients with Crohn’s disease. The pairwise t-test was done to compare the before and after intervention effect of performance ability in patients with Crohn’s disease. The results of this findings are as follows. Firstly, comparing the mean scores in the stress status, respondents’ score(52.07±0.82) after intervention a statistically significantly decreased than respondents(76.25±1.49) before intervention(t=1.94, p=.026). Secondly, this paper found that the performance ability in patients with Crohn’s disease was increased by 68.92-82.95% compared with the previous status. Therefore, this paper will provide framework of a system development for managing the patients with Crohn’s disease according to information system

In this paper, the numerical simulation of the two-dimensional and three-dimensional transient flow field in an oil-free scroll compressor is performed by the CFD dynamic mesh technique. During the procedure of simulation, the air in the scroll compressor is treated as ideal gas, and fit for the flow governing equations as well as gas state equation. In our approach, RNG k-ε model is used for turbulent model. The simulation results show that the flow field in the scroll compressor is time-periodic, in addition, the generation, motion and size change of the vortices inside the scroll compressor can be visualized. By contrasting the two-dimensional and three-dimensional flow field, the advantages and disadvantages are clearly found in simulation. The simulation not only extremely vividly reveals the scroll compressor inherent laws but also provides theoretical references for the optimal design of scroll compressors.

This paper proposes a new multiple open-switch fault diagnosis method and faulty switch localization algorithm in three-phase AC/DC PWM converter for permanent magnet synchronous generator (PMSG) based grid-connected wind power generation system. In the proposed scheme, the open-switch fault is detected by using normalized three-phase RMS currents and faulty switch location is identified by using normalized three-phase RMS currents as well as average phase currents. Various kinds of fault may occur in AC/DC PWM converter, which decreases the generator output power and degrades the stability in wind power generation system. In this paper, multiple as well as single open-switch fault conditions are investigated. The proposed fault detection and faulty switch localization algorithms do not require additional sensors or hardware since they use only the information on measured phase currents. In addition, they are quite simple, cost-effective and easy to use. To verify that the proposed methods are effective to detect faults and to identify the faulty switches position, the simulation results under twenty-one cases of open-switch faults are presented on different operating conditions.