Earticle

There are air gap and machining difficulty for loose coupled rotating transformer in contactless excitation system (CES). The coupling coefficient is relatively small compare with traditional transformer at the same time. There are several problems in the CES, such as loose coupled rotating transformer works inside the motor with high speed, difficult way to control, primary side and secondary side of loose coupled rotating transformer fix on the motor stator and rotor. In view of the adjacent windings type and coaxial windings type, the topology, simulation and experimental research are given in this paper. Through Ansoft 2D model identified two kinds of topology optimal working air gap is 1 mm. Verify the adjacent windings type topology of magnetic line of force closure degree is better than coaxial windings type. The simulation of Ansoft 3D model with adjacent type verifies the magnetic induction intensity is better than coaxial windings type. The experimental prototype of adjacent optimal type on CES to test the design has good transmission effect. The experimental results verify the rationality of the design of the adjacent windings type topology and accuracy, play a key role in improve the contactless excitation system in the future.

When looking for a way to develop a program with artificial intelligent, the most common related concept is the artificial neural network (ANN). Due to being a computational model of a biological neural network that can be used for simulating, processing or prediction. This article have as objective the mathematical implementation of a feedforward neural network in C# programming language. To achieve the previous, the behavior of a MATLAB ® neural network was analyzed, with the purpose of making the data adjustment that allows identify the energy consumption for a building from weather and time variables.

Machining impeller parts complex curved surface, the overall stiffness of the machine tool, tool position and orientation changes, the stiffness distribution of the workpiece will affect the processing system, thereby affecting the quality of the machined surface. In this paper, four-axis NC machining centers as a example, based on multi-body small deformation theory, through the point transfer matrix, the Jacobian matrix, etc. complete the system stiffness field modeling, and the introduction of three-dimensional force ellipsoid. under the different tool spatial gesture to establish an integrated processing system stiffness field, by force ellipsoid beam analysis tools, tool position and orientation of the tool, the tool spindle with the department, blades, etc. for stiffness performance impact of the system, analysis of the distribution of the stiffness characteristics of the blade surface. Finally, experiments show that the theoretical model can effectively optimize the impeller blades processes.

This paper considers the H∞ tracking control for a class of uncertain systems with time-delay and disturbance. The solvable sufficient conditions for the tracking control with state time delay are presented. The tracking controller is designed by using convex combination technique and Lyapunov functional method. The controller enables the system to meet the model reference H∞ tracking performance index. The delay-independent H∞ tracking control criteria is derived and formulated in the form of linear matrix inequality (LMI). A numerical simulation example is presented to verify the validity of the proposed method.

Unlike in the conventional RC method, prefabricated houses are prefabricated in the form of unit modules at a factory and assembled at a site. At the site, a ratchet wrench or an electric impact wrench is used to assemble the unit modules; however, their work efficiency is low, and construction tools including wrenches can often cause hazards for workers. In this study, an improvement plan is proposed by analyzing the problems of the existing assembly tools to enable the safer and more efficient assembly of modules. Through a structural analysis of the improvement plan for the assembly tools, it was found that the potential maximum stress of the tools did not exceed the yield stress of the steel.

With the increase of the magnetic valve controlled reactor capacity, winding loss brings more and more harm. Based on the physical model and mathematical model of magnetic valve controlled reactor, this paper proposes a valid method for calculating the winding loss .The proposed method calculates winding current harmonic content under different saturation, and obtains the leakage magnetic field distribution of magnetic distributed-valve reactor by using ANSYS. According to the leakage magnetic field distribution, winding loss can be calculated, and the loss curve can be deduced, which is only related to the saturation degree. The error between the ANSYS simulation results and the proposed method results is very small.

This paper presents a mathematical approach of the controlling of Unmanned Aerial Vehicle (UAV) translational and rotational movement dynamics by using classical regulation, pole-placement & tracking (RST) controller with model reference adaptive control (MRAC). Identification of a black box is done by using the Least Square Estimation (LSE) method while MIT rule is used as a control algorithm in conjunction with the RST controller with MRAC. The desired result of 6-degrees of freedom (DOF) via Multiple Input and Multiple Output (MIMO) model comprises the equation of motions which utilizes UAV to stabilize the nonlinear, translational and rotational movement implements the adaptive approach via initial conditions at the start of vertical takeoff. The numerical approach simplifies the control equations of the tri-rotor and stabilizes towards linearity. The resulted control strategy is affected over nonlinear simulation for each control dynamic and gives more stability with less power requirements. Hence the adaptive algorithm is ensuring the controlling and stability of the system.

Autonomous underwater vehicle (AUV) collaborative design platform which is a novel system to solve collaborative design problem of AUV is established. The platform hardware structure is introduced and the main sub-system named visual flow design system is described in detail. The function structure of visual flow design system is presented. Two main modules in the visual flow design system including flow modeling and flow monitoring are introduced. For flow modeling module, basic widgets and task widgets are designed to realize visual flow design and self-definition of computing tasks based on the workflow theory and XML technology. Flow monitoring module can realize real-time monitoring of flow state, flow execution time and IP of workstation assigned to each task. Flex-based visual flow design makes AUV collaborative design platform easy to use and helps the designers improve design efficiency and shorten development period.

In this paper, a computational model for hybrid systems is defined. Based on this model, a partial order relation of hybrid systems is given and a lattice of hybrid systems is formalized. Armed with these notations, synthesis of hybrid systems is discussed. The synthesis can be seen as the operation of solving the least upper bound of members of the lattice. An example is given to illustrate the approach.

In this thesis, a boost chopper using PV (Photovoltaics) system and PWM (Pulse Width Modulation) voltage type power converter were constructed to provide a pleasant environment to the patients in the hospital wards by controlling temperature, humidity and air-conditioning & heating. For the stable modulation of solar cell, synchronizing signal and control signal were processed using one chip microprocessor. Power converter system was constructed with booster chopper and voltage source inverter and test was carried out for both devices. Constant voltage control method was used to track a maximum power point at boost converter control. For the inverter control, synchronizing signal and control signal were processed by microprocessor for the stable modulation according to the switching theory of SPWM (Sinusoidal Pulse Width Modulation) and directions to each sector. Test was carried out for inverter control using SPWM control method. In addition, grid voltage was detected and this grid voltage and inverter output were operated at the same phase for the phase locking with PWM voltage source inverter so that surplus power could be linked to grid. This characteristic was applied on the temperature and humidity sensors in the general buildings and buildings having specific purposes such as hospitals. The good dynamic characteristic of inverter could be obtained by these applications. Also, PWM voltage inverter maintains a high power factor and low-frequency harmonic output so that power can be supplied in the load as well as system.

According to the uncertainty problem in the process of quad-rotor aircraft flight, As close to the actual flight environment, The nonlinear dynamic model of quad-rotor aircraft is established,On the basis of the backstepping, Analyzed the presence of interference control quantity expression and adaptive law.This paper puts forward a technique of backstepping and adaptive control technology,Through Matlab simulation and flight test of the designed adaptive inverse footwork the effectiveness of the proposed controller is verified, The simulation results show that the system has good robustness.

In this study was conducted with focus on the change in vibration characteristics in the rail to analyze the noise produced in the rail upon operation of slide mechanism in power seat for vehicles. Preferentially, the motor rpm was simultaneously measured about operating noise, vibration as operating into direction of forward and backward with the slide mechanism. And, modal test was conducted according to operation position of the seat rail, through which overall analysis was conducted for the effects of vibration characteristics of the rail on operating to noise. According to the results, it could be seen that resonance occurred between the 2nd natural frequency generated on the left upper rail and the 3rd order of motor rotation to affect the operating noise.

Aiming at the market shares of automatic mechanical transmission, the driving smoothness was studied. Based on the dynamical model of automatic mechanical transmission, the numerical model of automatic mechanical transmission had been established and a shifting strategy was analyzed. The result shows that the impact of automatic mechanical transmission on the condition of shifting fast can meet the national legislation.

The energy performance of sensor nodes which are deployed in arbitrary regions in sensor networks is an important issue. Clustering of the network is a method to make nodes to groups based on geographical position. Nodes on the clustering sensor networks can reduces the communication traffics of inter-node communications and raises energy efficiency by transmitting the collected data to the cluster head for sending finally to the sink. Nevertheless, due to radio channels used on clusters, interference and collision of frequency can occur between neighboring clusters. The channel collision increases energy consumption due to waste of communications. The occurring of frequency interference and channel collisions among neighbor clusters can be resolved by assigning non-overlapping channels among neighbor clusters. In this study, a channel allocation algorithm based on the four-channels is proposed. It allocates exclusive channels among neighbor clusters those implicate various polygonal shapes. Allocating channels in complicate clustering topologies, a local hole which is surrounded by four different channels can be appeared. To solve this local problem, an algorithm which has main and local parts is proposed. The proposed algorithm is applied to a complicate network. The result of experiment shows that the proposed method assigns succes

Permanent magnet synchronous motor (PMSM) can appear chaos phenomenon when PMSM in turn on or turn off. When control chaotic PMSM to zero, the state variables of the system can appear fluctuate which is not the ideal control result. In order to overcome fluctuate in control chaos. This paper propose adaptive backstepping of error compensation to control chaotic PMSM, an error compensation item is developed in the virtual control design of each backstepping step to compensate the effect of unknown error dynamics on system for obtaining smooth process of chaos control. This scheme can eliminate oscillation in course of control chaos. Numerical simulations further test the effectiveness of the theoretical analysis.

Permanent magnetic actuator, for its various advantages such as high motion reliability and time accuracy, lays the foundation for the development of the synchronous control technology of circuit breaker. This paper designs a synchronous controller for the vacuum circuit breaker of 126kV. First of all, it identifies the principles and basic requirements of the synchronous control technology, based on which the grid signals are pre-processed. Secondly, white noises are removed and interfering signals are filtered by FIR digital filter so that signal zero can be accurately detected by applying the linear interpolation method. Then, the mathematical model for closing time under different voltages and temperatures are established using BP neural network technique. Later, weight and threshold are adjusted by applying L-M algorithm to conduct basic training and test for the neural network so that the opening and closing times can be compensated. Finally, FFT (fast Fourier transform) is used to calculate signal frequency and phase. Then the synchronous controller f the design undergoes the accuracy test. The result shows that the error of synchronous control is limited to less than ±1ms.

In order to share train safety information when trains pass through long tunnels, steep curves and single tracks, it is important to develop a real-time two-way auxiliary communications system. This study would examine the possibility of the rail tracks as the transmission lines of PLC (Power Line Communication). Moreover, the data transmission characteristics of rail track PLC by distance were evaluated. Sustainable channel transmissions were 12 to 20 MHz and 25 to 33 MHz. Furthermore, experimental results showed that the signal attenuation at each frequency of 5, 10, 15, and 20 MHz is constant within 5%. This result shows that PLC, when using 50 m of rail track, can be applied commercially within the signal attenuation threshold of -70 dBm.

It is well known that condition based preventive maintenance (CBM) plays a key role in improving reliability of the devices and increasing security of the production process. But compared with traditional time based preventive maintenance (TBM), due to being an unplanned examining-maintenance activity beforehand, stationary operation of the devices is possibly interrupted so as to make whole production process become unstable, for example, connected-grid wind power generators, large-size nuclear power facilities, and railway transportation signals, and etc. Hence, in this paper the full life cycle model of the devices operation is firstly constructed with preventive maintenance (PM) involved, and then its reliability indexes and steady-state operation characteristics are analyzed with the model parameters being time-invariant corresponding to TBM. On the basis of it, the operation behavior of time-variant system is researched corresponding to CBM under some limitations, such as stability, accessibility, and controllability, and etc. The investigations indicate that TBM is a predictable and controllable process such that it can satisfy one’s expectation by selecting suitable model parameters, whereas CBM is usually unpredictable such that it can not arrive at desired aim. Therefore, based on the relationships of the two, this paper proposes a CBM control scheme based on TBM, and investigates the dynamical behavior and real-time characteristics of control systems. The goal to do this makes the CBM exhibit some expected behaviors like the TBM such that the behaviors of the time-variant system can meet the desired requirements. The investigation results show that the proposed technology is quite effective, and is fit to control stationary operating of the systems under CBM scene. And so the proposed method possesses certain theory instruction significances for PM maintenance practices for those large-scale production processes.

Nowadays, Geographic Information System (GIS) has been widely used in traffic control or urban planning and monitoring, thus, remote sensing images should be processed in digital form, which allows rapid integration of remote sensing analysis into a GIS. This paper discusses an image processing approach by using lifting wavelet and curvelet transform to carry out the image fusion of remote sensing photos. This approach integrates the lifting wavelet and curvelet transform to deal with the challenges in remote sensing image fusion. Experiments are carried out for testing the feasibility and compare the proposed approach with traditional wavelet manner. The experimental results show that, the correlation coefficients of primary low waveband from the proposed model are a little bit higher than the panchromatic waveband. That implies the image fusion can be performed better by the proposed model. Additionally, it was found that, the enhancement of information entropy will be improved by 7.73% and 9.84% respectively from both two experiments.

Energy efficient Data Aggregation Scheduling is essential in Ubiquitous sensor networks. Optimal communication distances between the nodes and the base station improves the network lifetime. Clustering improves the efficiency of the data aggregation problem. Many clustering techniques exist to find the optimal number of clusters in the network. The computation complexity of the methods to obtain optimal number of clusters is fair when genetic approaches are employed instead of the classical approaches. Since nodes in USN are dynamic, finding data aggregation schedules is difficult in a USN. Concurrent transmissions improve the throughput of the network, but the SINR perceived at the receiver should be greater than or equal to a certain threshold value for a successful transmission. Also the cluster heads and the member nodes dissipate energy. This power dissipation is more when there are more number of cluster heads. The noise and the power dissipation play a major role in decreasing the network life time. Hence in this paper we designed an efficient energy dissipation algorithm for data aggregation scheduling using the principles of Genetic algorithm and SINR. Since the battery power and bandwidth are the limited resources for the nodes in the USN our data aggregation scheduling algorithm gives equal priority for all of the following while electing a node as a cluster head. They are (a) Total power dissipation from all cluster heads in the USN, (b) The total power dissipation from the nodes at each cluster heads, (c) The SINR perceived at the cluster head should be more than a threshold value at each cluster head for the transmission to be successful, (d) The optimal schedule for the nodes in the USN so that all the nodes transmits their data finally to the base station quickly. With the application of the genetic methods our algorithm proved to be efficient when compared with the existing algorithms in obtaining maximum network life time with minimum number of clusters.

In this paper, the problem of delay-dependent condition for a new class of Takagi-Sugeno (T-S) fuzzy Lurie control systems with multiple time-delays is discussed. Proper Lyapunov functions are defined by using the Lyapunov stability theory, and a novel delay-dependent absolute stability condition is derived with the linear matrix inequality (LMI) and free-weighting matrix approach, which is different from previous research. Meanwhile,a numerical example is provided to demonstrate feasibility and effectiveness of the proposed result by using the LMI and Simulink toolboxes in MATLAB, and the value of time delay has proved less conservativeness of this method.

In video action recognition, the Dollar detector has been widely used to extract Spatio-Temporal Interest Points (STIPs) from action video sequence. It generates two kinds of information: STIP position and the respond value. However, in many cases, the detector respond, which measures the strength of local motion changes, is ignored. By utilizing such information, we propose to build a Hierarchical STIP Saliency (HSS) framework to provide different types of motion information. A novel local feature named Mixed Neighborhood Feature (MNF), which integrates the similarity and position relationship between local features, is put forward, and encoded by localityconstrained linear coding. Then, by partitioning video sequence along temporal direction, a group of sub-STVs are produced, and their corresponding descriptors are obtained with a max-pooling-on-absolute-value technique. In classification stage, Locality-constrained Group Sparse Representation (LGSR) is adopted as classifier to utilize the intrinsic group information of these sub-STV features. The experiments on the KTH and UCF Sports datasets show that in contrast to the classical recognition systems published recently, our recognition system based on the HSS and MNF achieves good performance.

The bottom hole pressure should be controlled during the pipe connection procedure in a drilling operation to prevent the possibility of oil well blow out, to avoid the collapse of the well and to prevent the fracturing of the bore walls. It should be maintained within a window defined by the collapse pressure as the lower limit and by the fracture pressure as the upper limit. This paper describes the use of a nonlinear model predictive controller (NMPC) to maintain the bottom hole pressure. In addition to a topside choke valve, backpressure pump is also used as a control input. While connecting an additional pipe segment, the injection of the drill fluid is completely stopped. The drill fluid pulse telemetry system that is used in the measurement and transmission of the bottom hole pressure may not function properly and there will be absence of signal while the pipe is being connected. A nonlinear estimator, the unscented Kalman filter (UKF) is used for the continuous estimation of the fluid flows and pressures at different sections of the well being drilled. Simulation results show that the bottom hole pressure can be managed effectively during the drilling of an oil well with nonlinear estimation and control.

Structural controllability is an important concept of linear systems, and problems relating to this concept have recently become the subject of a great deal of research. In this paper, two different structures of control are proposed that are based on the servo control system. An analysis is conducted on the structural controllability of two control systems, the differences of which relate to the structural controllability criterion in the frequency domain over F(z). Due to the fact that the system is not structurally controllable, the first servo control system is not completely manageable no matter what values the parameters take; therefore, the reasons for this are investigated. Conversely, the second system becomes structurally controllable by changing the structure of the control system. Thus, it is made fully stable by the feedback compensation even if it has an unstable mode. Accordingly, this research on the structural controllability of a system not only provides a deeper understanding of the system’s nature, but is also important for explaining why a system is not structurally controllable and how changing its structure can resolve this.

In order to solve the uncertain problem that parameters of system model are not accurate, a synchronous control method which is based on sliding mode method is proposed in this paper. A synchronous system which has the similar structures with the controlled system is constructed, then a control law is design to make the synchronous system trace the controlled system. So the controlled system can be controlled by controlling the synchronous system. Finally, numerical simulation was done the testify the rightness of the proposed method.

Comparative investigations of the conventional analog and optical communication analog fire detector signal attenuations with various numbers of fire detectors were performed in this research. The conventional fire detector signals with 1, 2, 16 and 32 fire detectors were 4.5, 4.0, 2.2 and 0.8 V, respectively. The fire detector signals were drastically decreased with the increase of the number of fire detectors. However, the optical communication fire detector signals were not changed with increasing the number of fire detectors. Therefore, optical communication fire detector system is a promising fire detection system for eliminating the false alarms.

Boiler deaerator system was introduced in this paper, the dynamic characteristics of the system was analyzed, the transfer function of the system was obtained.According to the system time’s delay and non-linearity, the fuzzy adaptive tuning PID control strategy was formulated, the system simulation was completed by MATLAB . Experimental simulation results of MATLAB show that the fuzzy adaptive tuning PID control can complete system control better, and obtain better dynamic and static performance.

This paper presents an improved Cubature Kalman filter (CKF) for strap-down inertial navigation system (SINS) initial alignment. In order to enhance the stability and precision of the filter, Newton iteration algorithm and square-root strategy are blended into CKF. Iterative Square-root Cubature Kalman Filter (ISRCKF)makes full use of latest measurement information and directly employs the square root of covariance matrix for recursive update in the iterative process. ISRCKF can effectively avoid non-positive covariance matrix and improve the estimation accuracy. Simulation results show that ISRCKF performs well for SINS initial alignment with large azimuth misalignment.

Driving fatigue is a common occupational hazard for any long distance or professional driver, and fatigue detecting has major implications for transportation safety. Monitoring physiological signal while driving can provide the possibility to detect the fatigue and give the necessary warning. In this paper, fifty subjects participated in driving simulations experiment with their recorded EEG signals to induce two kinds of fatigue states: Alert and drowsy. Two nonlinear methods, approximate Entropy (AE) and Sample Entropy (SE), were used to characterize irregularity and complexity of EEG data. Subsequently Support Vector Machine (SVM) was applied to classify these two fatigue states. The experimental result shows that two complexity parameters are significantly decreased as the fatigue level increases. The result indicates that both of two nonlinear indicators can be used to characterize driver fatigue level. Furthermore, the combined measure feature results in higher classification accuracy, indicating the proposed classification method is more robust and effective, compared with single complexity measure.