Applied Mechanics and Materials Vols. 397-400

Abstract: To realize the real-time temperature measure and control rapidly and accurately in the incubator, a temperature measurement, control and display system is designed in the paper by using of the smart temperature sensor DS18B20 and the microcontroller AT89S52. The output mode of DS18B20 is serial in one-way, and its main function is to transform the temperature into the digital data and store the control word of the output conversion accuracy, which is available for data processing of single-chip microcomputer. In the actual temperature measurement it doesnt require any extra components including backup power supply, and the user can also choose the resolution. It is easy to realize multi-point measurement, connect and extend the real-time measure data. The system circuit can be applied to any field which needs multi-point measurement and real-time detection.

Abstract: Rolling bearings are common parts in the transmission systems and have been widely used in various kinds of applications. The normal operation of the rolling bearings hence plays an important role on the efficiency of the system performance. However, due to hostile working environment the rolling bearings are prone to failures. The transmission systems may break down when there occurs faults in the rolling bearings. As a result, it is essential to detect the faults of rolling bearings. However, when use artificial intelligence method to diagnose the rolling bearings faults the signal processing is extensively complex while very few works have been done on the simplification of the artificial neural network (ANN) models for the rolling bearings fault detection. To deal with this problem, a simple self-organized map (SOM) neural network method together with a principal component analysis (PCA) based feature reduction procedure is proposed to diagnosis rolling bearings faults in this work. The vibration data of the normal and faulty rolling bearings was acquired from an experimental test bed. The PCA was firstly used to extract distinct fault features. Then the SOM was employed to train and learn the fault features to identify the fault patterns. The fault detection results show that the proposed method is feasible and effective for the fault diagnosis of rolling bearings. The fault detection rate is beyond 89.0%.

Abstract: The pickling process is the important metallurgical production process. Based on pickling process prediction model, considering the max economic efficiency as the optimized objective, and seeing the operating variables as the decision variables, this paper establishes the pickling process optimization model and makes the optimized calculation to get the value of each key control circuit. At the same time, considering the pickling process prediction model error brings the uncertainty to the optimization results, based on iterative optimization control thoughts do pickling process optimization control, the simulation results verify the effectiveness of the method.

Abstract: The basis of the paper is that there are already some methods to accurately evaluate, test and diagnose the performance of the model predictive controller. And the result shows the reason of a bad performance of control system is because of model mismatch. There are much more complexity and variety in the problem of multiple mismatched parameters than single mismatched parameter, so we need consider more factors about it on the basis of the solution of single mismatched parameter. We propose a way of adjusting model parameters based on fuzzy rules when there are more than one mismatched parameters. The method is to adjust the step-size of parameters and get the adjustment rules on the basis of the changes of maximum overshoot, rising time and settling time. The last, verifying the method is effective by experiments.

Abstract: In this paper, the application of fuzzy control algorithm in duct active noise control technology was studied, according to the problem of secondary acoustical feedback existing in feedforward control structure (FCS) adaptive active noise control (AANC) system, a reverse control structure of fuzzy active noise control (FANC) system was established. Through Matlab software the fuzzy control algorithm was simulated, and the simulation results showed that it has a good convergence and stability in the FANC system.

Abstract: Fuzzy control does not have a precise mathematical model, but it is a very effective way to deal with complex systems stability problems. Firstly, a class of uncertain fuzzy systems is given, and in this class model the parallel distributed compensation (PDC) controller switching method is introduced. Next, the methods of single Lyapunov function and multi Lyapunov functions are respectively used to obtain the conditions which make the closed-loop system asymptotically stable. Finally using the MATLAB/SIMULINK software to simulate, verify the feasibility and effectiveness of the theoretical derivation.

Abstract: Finite-time chaos control of Lorenz chaotic system applying the passive control method is investigated in this paper. Based on the finite-time stability theory and the passive control technique, the passive controller are proposed to realize finite-time chaos control of Lorenz chaotic system. The controller is robust to noise. Both theoretical and numerical simulations show the effectiveness of the proposed method.

Abstract: A control method is proposed to improve vehicle yaw stability by the integrated control of yaw moment control. The control strategy using feedback compensator is proposed, which produces direct yaw moment and front steering angle to control yaw rate, by actively controlling the front steering angle, the integrated control system makes the performance of the actual vehicle model follow that of an ideal vehicle model. A experiment is performed at different conditions, the results showed the presented method can effectively control the yaw rate, and at the same time lighten the burden of the driver. Key words: EPS; Yaw rate feedback; Vehicle stability

Abstract: In order to realize the guidance and control of the flight system, we focused on the study of different guidance instructions extraction methods and system stability control problems with respect to the characteristics of full-strapdown optical imaging seeker. First, we established the model of strapdown optical imaging seeker and introduced the definition of scale factor and the theoretical compute formula. Then the full field of view accuracy of full-strapdown optical imaging seeker was gained through the experiment and the validity of the scale factor definition has been tested and verified. Finally, we analyzed the system stabilities of different guidance instructions extraction methods. The results showed that if we applied the line of sight angular rate (LOS angular rate) to the system, the scale factor error was 5% when the free-running frequency of the overload autopilot was 20rad/s, and the scale factor error was 8.4% when the free-running frequency was 10rad/s. And if we applied the line of sight angle (LOS angle) to the system, the scale factor error was 33.3%, irrelevant to the free-running frequency. This analysis laid a foundation of guidance application..

Abstract: Considering that multivariate data is difficult to detect, this paper propose an PLS and Bayesian theory based on-line outlier detection method. Firstly, it figures out the Q-statistics by PLS(partial least squares analysis), then classify Q statistics with Bayesian classification method and decide whether or not the sample data is normal. We employ UCI database to verify the method, the simulation results show that, compared to traditional PCA based method, it has lower ratio of error judgement, and is more effective in detecting outliers and identifying the change of process states.