Earticle

Automobile exhaust emissions is one of the important pollution sources. How to reduce automobile emission is a hot topic in the research field. Research on the alternative fuel and alternative fuel engine has great potential application. CNG engine is more promising due to its less emission and relatively rich resource. Existing research on the combustion process of CNG engine realize that the performance is affected by the boundary conditions, and the ignition time is a key parameter in reducing the emission and improving the efficiency. In this paper, an adaptive control method, which is based on radial basis (RBF) network method, has been proposed for the optimal ignition advance angle. According to the training sample, the simulation results have great coincidence with the experiment results. According to the experiment, the necessity of the control method is proven, and the validity of the RBF neural network applied in the calculation of the ignition advance angle has been proven.

Application of the high voltage direct current (HVDC) system has been gradually extended due to many advantages compared to the high voltage alternate current (HVAC) system. Basically, the HVDC system has the current controller and voltage controller at the terminals of the rectifier and inverter, respectively. The control system should be properly applied to operate stably the HVDC system that depends on the system condition. That is, improving the characteristics of the control system may be needed during the transient state. In this paper, a new algorithm for improving the transient state of the HVDC systems under fault condition is proposed. The proposed control algorithm can change the control strategy of the converter. From simulations, the performance of the proposed algorithm is verified under the fault condition in the AC system.

A brushless DC motor is a nonlinear system with strong couplings and multiple variables,which is difficult to establish its accurate mathematical model. In the paper, based on the analysis of brushless DC motor control systems, a adaptive fuzzy PID intelligent controller is established, in which fuzzy control theories are combined with PID control methods, making full use of super computing and reasoning abilities of digital signal processors. PID parameters can be automatically adjusted according to the actual response of fuzzy reasoning. The experimental results show that the system has a better robustness and faster response speed compared with systems with traditional PID controls.

The design of a low frequency calibration shaking table is introduced in this paper. First, we confirm the design specification of low frequency calibration environment of vibration specification, we choose shaking sensor. Then, the design of the relative velocity feedback analyzes this method in detail and carry out the simulation table according to the national standard and the deployment a vibration exciter is introduced. According to the design method as the control method of the shaking table. We did simulation and calculation. Finally, we test the amplitude versus frequency response characteristics and distortion under the situation of open loop and closed loop. The results show that the low frequency movement signal of low frequency shaking table is improved and it can meet the requirement of the calibration of low frequency vibration sensor.

Aiming at the becoming, uncertainty and space distributing of input multi-fault characteristic information in train intelligent control system fault diagnosis, a system structure for fault diagnosis of multi-information fusion in train intelligent control system is presented. The method of fault diagnosis of multi-information fusion in train intelligent control system based on fuzzy neural network and D-S evidential theory is discussed. Result of example indicates that this method can effectively improve the probability and reduce the uncertainty of diagnosis.

This study presents an improved doubly fed induction generator (DFIG) that is integrated with a battery energy storage system (BESS) for microgrid control. The proposed DFIG can generate independently the power output of the rotor-side converter (RSC), grid-side converter (GSC), and battery-side converter. The maximum power point tracking (MPPT) is included in the RSC to maximize the generated power of DFIGURE. The power of the GSC is used to smooth total wind power of DFIG and to maintain stably AC voltage and frequency in the island mode. The battery-side converter is used to keep the dc link voltage of a back-to-back converter. The effective of the proposed DFIG is validated by simulations on Matlab / Simulink environment.

A new data-driven condition monitoring method for wind turbines is proposed to prevent a turbine failure in a wind farm. The method works through the power curve model which is built with historical SCADA data. New constraints that established based on Betz’ law and RC model are developed for governing the power curve model. Since abnormal data has a strong impact on the power curve model, the Inner-DBSCAN algorithm is proposed to reject it. In addition, we use an edge recognition method for normal data to form the power curve model. Then, the turbine operation condition can be monitored through the model. Its effectiveness through industrial studies is confirmed, and the time cost of building the power curve model is only 1.08s.

The processing of forming deep hole in sheet is a kind of process using friction heat between drilling tool and workpiece to make workpiece in plastic deformation to machine hole. The process is a kind of green mechanical processing without chip. Studying green processing process in mechanical is becoming a development direction. In this paper, simulated analysis about the influence of processing parameters on the friction heat and the shape of forming hole, and researched on the temperature area of warm forming to machine hole, and then studied on quality of the hole in different temperature area in order to determine the appropriate warm extrusion temperature; Finally contrasted analysis the size of the hole of different location of test and simulation. The research results show that the simulation results agree well with the actual test results, and the warm extrusion is useful to form hole under the condition of a certain thickness.

In this paper an adaptive robust control scheme along with its simulation on quadrotor is presented to deal with payload variation and unknown disturbance. Parametric and nonparametric uncertainties in the quadrotor model always make it difficult to design a controller to meet the performance requirement in various conditions during flight time. Adaptive robust backstepping (ARB) control, which is based on improved Lyapunov theory, is suggested to solve the problem. The proposed control scheme introduces piecewise functions into parameter adaptation law and control law to avoid control chattering while the Lyapunov function uniformly bounded is used. This choice not only provides guaranteed transient and asymptotic tracking performance but also precisely estimates the system parameters. Promising simulation results in different environments are carried out to demonstrate the efficiency and robustness of ARB control, and its advantages are indicated in comparison with conventional PID controller.