Guoyong Huang

An attitude control method of unmanned helicopter based on adaptive output feedback

The unmanned helicopter exhibits a complex and nonlinear dynamic behavior and open-loop unstable. This paper describes a attitude control method based on adaptive output feedback for an unmanned helicopter. First, it is assumed that the controlled system satisfies the output feedback linearization conditions. Second, the approximate model of the system is considered as the diffeomorphism of the system. Then, a linear controller and adaptive neural networks are designed to cancel the model errors produced by nonlinear, uncertainty and disturbance. Finally, the boundedness of tracking errors and weight errors are studied with Lyapunov stability theorem. The application results of an unmanned helicopter show that the proposed controller can not only cancel the dynamical error effectively but also improve tracking performance of the attitude control system.

Research on Pattern Recognition Method of Blockage Signal in Pipeline Based on LMD Information Entropy and ELM

Aiming at the nonstationary and nonlinear characteristics of acoustic impulse response signal in pipeline blockage and the difficulty in identifying the different degrees of blockage, this paper proposed a pattern recognition method based on local mean decomposition (LMD), information entropy theory, and extreme learning machine (ELM). Firstly, the impulse response signals of pipeline extracted in different operating conditions were decomposed with LMD method into a series of product functions (PFs). Secondly, based on the information entropy theory, the appropriate energy entropy, singular spectrum entropy, power spectrum entropy, and Hilbert spectrum entropy were extracted as the input feature vectors. Finally, ELM was introduced for classification of pipeline blockage. Through the analysis of acoustic impulse response signal collected under the condition of health and different degrees of blockages in pipeline, the results show that the proposed method can well characterize the state information. Also, it has a great advantage in terms of accuracy and it is time consuming when compared with the support vector machine (SVM) and BP (backpropagation) model.

Research on moving target detection algorithm based on MRA and wavelet threshold

Aiming at solving the noise problem which had lowered the accuracy in the target detection result from the process of image-collection and image-transmission, the paper proposes a new target detection algorithm based on the improved wavelet threshold. Firstly, these images are filtered by a denoising method, which combines the wavelet threshold method with the correlation of the wavelet coefficients, and its “Zoom” feature can eliminate the negative impact of noise; then a combined algorithm which connects background subtraction and two consecutive inter-frame subtraction is set up in order to combine their advantages and improve the effect of target detection. Compared simulation results of the four models, the results show that the target detection method based on multi-scale wavelet threshold is reasonable and effective, and more suitable for the real-time target detection.

Approach to fault feature extractions of rolling bearing via EEMD and full-vector envelope spectrum

Misjudgments and missed judgment widely occur during the fault detections of rolling bearing due to the fact that single-channel vibration signal information is often collected incomprehensively. In order to recognize bearing faults as possible, a method is proposed that features the combination of Ensemble Empirical Mode Decomposition (EEMD) and full-vector envelope spectrum through the following steps. Firstly, the two homologous double-channel fault signals of bearings undergo EEMD decomposition individually. Then intrinsic mode functions (IMF) with the maximum and secondary kurtosis values at all directions are selected as the reconstructed signals. Finally the reconstructed signals are subjected to full-vector envelope fusion by the use of full-vector envelope spectrum so that the fault feature frequency of bearings can be extracted. By the use of the present method, the real vibration state of rolling bearing were reflected objectively, and the fault feature frequencies of rolling bearing were extracted effectively for the purpose of recognizing fault types, as the experiment results showed.

Research on cycle slip detection based on difference morphology filter and singular value entropy

In order to solve the problem of Beidou cycle slip detection during Beidou navigation process, a method based on a morphological filter and singular value entropy is proposed to detect the cycle slip in this paper. Firstly, the difference morphological filter is used to denoise the cycle slip signal. Then, the singular value decomposition (SVD) is used to decompose the de-noising signal and obtain several feature sets. Finally, the singular value entropy is obtained for the original feature set to reflect the state of cycle slip. The experimental results show that the proposed method can effectively detect cycle slip information.

Phase reduce false distance law and ionosphere residual error method detect and correct the cycle slip

During GNSS precision positioning data processing, the detection and correction of the cycle slip has been a core problem all along. Aiming at the disadvantages that there are some multi-value problems in the cycle-slip detection of the ionosphere residual error method and the phase reduce false distance low is not sensitive to the small cycle slip, this paper puts forward combining both methods to deal with the cycle slip. The case analysis indicates that the principle of this combination method is simple; the calculation speed is fast; it has strong practicability.

Small cycle-slip detection of single-frequency in BDS based on SVD

To accurately detect and position small cycle slip is critical for high-precision BeiDou Navigation Satellite System (BDS) data processing. Thus, a method based on singular value decomposition (SVD) was proposed in this paper for detecting single-frequency small cycle-slip. First of all, detectable quantity of cycle-slip was measured according to observations of pseudo-range and carrier-phase. Then, a track matrix of attractors was constructed with Hankel matrix and processed with SVD to determine the singular value that reflected abrupt information. At last, signal components were reconstructed by inverse operations and transformation of reflexive space through SVD to detect cycle-slip pursuant to the position of signals in case of the maximum value. The experimental results suggested that the method put forward in this paper was effective for precisely detecting small cycle-slip within one to five cycles based on observations of single-frequency carrier-phase.

Improvement on asynchronous motor system identification based on interactive MRAS

Aiming at the inaccurate estimated rotate speed resulting from the parametric variation of the asynchronous motor, this paper designs an estimation method of the Model Reference Adaptive System (MRAS) that can identify the stator resistance and rotate speed simultaneously, and replaces PI link with sliding-mode control based on the approaching rate aiming at the complex PI gain coefficient adjustment existing in the common MRAS estimation method. This method can estimate the stator resistance and rotate speed value of the asynchronous motor during the operation only by detecting the stator side voltage and current, so as to make the whole system gain strong robustness on the change of the stator resistance, and improve the control accuracy of the whole system. The simulation experiment through the vector control on the asynchronous motor verifies the accuracy of the mentioned methods.

Internal and sliding mode current decoupling control of asynchronous motor

After the vector control of the asynchronous motor goes through the coordinate transformation, the cross coupling still exists between d and q axis in the electric current loop, and the coupling weight increases with the synchronizing frequency. There is coupling and retardation in traditional PI controller. The voltage feedforward decoupling is sensitive to the parameters. Therefore, it is feasible to design a current decoupling control method with the integration of internal and sliding mode. Realize the dynamic decoupling towards the current through the internal mode control; adopt the insensitive characteristics of the sliding mode control towards the parameter change, so as to inhibit the influence of the parameter perturbation and external disturbance, and improve the robustness of the system. The simulation result indicates that this method can effectively realize the dynamic decoupling of the current and improve the dynamic performance of the system. Besides, it has good robustness.

Design of pipeline displacement detecting system based on ZigBee wireless sensor networks

Most of the gravity-dropped slurry pipelines are underlaid in mountainous areas which are vulnerable to disasters, such as debris flow and landslide. The accumulation of displacement of the pipeline caused by those disasters is very likely to cause pipeline fracture. To solve this problem, a design of detection system for displacement of the pipe which is based on ZigBee wireless sensor network and MEMS accelerometer be put forward. This system adopts modular design which includes central processing unit, data acquisition module, serial communication module and human-computer interface. Different detecting points of the pipeline can realize wireless networking and communication by ZigBee Protocol stack. Detecting points use sensor collecting displacement data and uploading data by wireless network step-by-step, last through serial port to upper computer in central control room and display, save it. And according to those data, it can issue warnings in the event of exceeding threshold. Experiments show that the system has a good stability of communication and can collect pipeline displacement data effectively, when the displacement of pipeline exceeding a threshold, it can effective issue warnings.