DISTRIBUTION OF ROOTS OF CUBIC EQUATIONS

Deqing Huang,Yilei Tang,Weinian Zhang 한국수학교육학회 2010 純粹 및 應用數學 Vol.17 No.2

In this note the distribution of roots of cubic equations in contrast to 0is given, which is useful to discuss eigenvalues for qualitative properties of differential equations.

Iterative Learning Control of Linear Distributed Parameter Systems.Frequency Domain Design and Analysis

Deqing Huang,Xuefang Li,Jian-Xin Xu,Chao Xu 제어로봇시스템학회 2013 제어로봇시스템학회 국제학술대회 논문집 Vol.2013 No.10

This paper aims at iterative learning control (ILC) design and analysis for a class of linear distributed parameter systems (DPSs) that may be hyperbolic, parabolic, or elliptic, and include many important physical processes such as diffusion, vibration, heat conduction and wave propagation as special cases. Owing to the linear characteristic of systems, the system equations are first cast into a matrix form in the Laplace transform domain. Then, through determination of a fundamental matrix, the system transfer function is precisely evaluated in a closed form. The derived transfer function clearly demonstrates the input-output relationship of system, and thus facilitates the consequent ILC design and convergence analysis in the frequency domain. The proposed control design scheme is able to deal with parametric and non-parametric uncertainties and makes full use of the process repetition, while avoids any simplification or discretization for the 3D dynamics of distributed parameter systems in the time, space, and iteration domains. In the end, an illustrative example is presented to demonstrate the efficacy of the proposed ILC scheme.

Generic Adaptive Sliding Mode Control for a Quadrotor UAV System Subject to Severe Parametric Uncertainties and Fully Unknown External Disturbance

Tianpeng Huang,Deqing Huang,Zhikai Wang,Xi Dai,Awais Shah 제어·로봇·시스템학회 2021 International Journal of Control, Automation, and Vol.19 No.2

This paper aims to provide a generic robust controller that is able to manipulate all kinds of quadrotor unmanned aerial vehicle (UAV) systems automatically or adaptively in the presence of severe parametric uncertainties and fully unknown external disturbance. The dynamic model of the quadrotor is first obtained using Newton-Euler equations. Then, considering the underactuated and the strongly coupled characteristics of the quadrotor system, a nonlinear adaptive sliding mode control (ASMC) scheme is proposed. Meanwhile, additional adaptive laws are designed to estimate all the parameters of the quadrotor system, which in principle are difficult to be measured directly and accurately. Furthermore, to guarantee the asymptotic stability of the closed-loop system, the upper bound of the fully unknown external disturbance is estimated and adopted as the switching gain of the ASMC. Finally, simulations and experiments are carried out to illustrate the effectiveness and robustness of the proposed control scheme, where the superiority to linear quadratic control (LQR) and active disturbance rejection control (ADRC) has been demonstrated clearly.

Guaranteed Cost Optimal Control of High-speed Train with Time-delay in Cruise Phase

Xiangjin Tian,Deqing Huang,Na Qin,Zifeng Gong,Qingyuan Wang 제어·로봇·시스템학회 2021 International Journal of Control, Automation, and Vol.19 No.9

In this paper, a novel guaranteed cost control scheme that takes into account state time-delay and parametric uncertainties is proposed for high-speed train (HST) optimal operation control. First, a linear dynamic model of HST is built, where the basic and additional resistances, in-train force, train effort as well as state time-delay are addressed explicitly. Second, an operation criterion considering the velocity tracking, operation safety and running cost is established. Third, a guaranteed cost controller is then designed to realize the optimal control with tradeoff among the multiple objectives. To the best knowledge of the authors, it is the first time to address the velocity tracking, the operation safety and the running cost simultaneously while considering both state time-delay and parametric uncertainties, which corresponds to a more practical scenario in high-speed train control. At last, simulation is carried out to validate the effectiveness of the proposed control scheme under different delay degrees.

Improvement of protein bait produced from beer yeast waste for controlling Bactrocera dorsalis (Diptera: Tephritidae) in China

Wang Bo,Huang Zongfang,Yang Deqing,Ji Qinge,Cai Pumo 한국응용곤충학회 2021 Journal of Asia-Pacific Entomology Vol.24 No.3

In the present study, preservatives and antibiotics were applied in a variety of doses to assess their effects on the beer waste-based protein bait, a product widely used to control populations of Bactrocera dorsalis (Diptera: Tephritidae). Screening was performed using the inhibition zone method against the dominant bacteria in deteriorated protein bait. Additionally, the attractiveness of the bait was assessed after respectively adding different doses of methyl eugenol, brown sugar solution, ammonium acetate, and guava essence, as determined by bio-cage tests. The results showed that the four selected preservatives had different inhibition effects at different dose levels, and that the level of inhibition increased with dose: at the highest dose of 1:1 (v:v), sodium benzoate can significantly inhibit Staphylococcus spp., potassium sorbate can significantly inhibit Lactobacillus spp., sodium nitrite can significantly inhibit Escherichia spp. and ethyl p-hydroxybenzoate can significantly inhibit Staphylococcus spp. and Xanthomonas spp. Among three antibiotics, kanamycin was the most effective in suppressing a mix of all four bacteria for all tested doses. In terms of lure performance, the addition of four substances in various ratios into the protein bait were found to have varying effects on its attractiveness to B. dorsalis females and males. Specifically, the addition of a high-dose of guava essence could significantly enhance the attractiveness of the bait. Our findings will help to enhance the effectiveness of protein bait ap plications by prolonging the quality guarantee period and improving its attractiveness toward both female and male B. dorsalis.

Adaptive Nonsingular Terminal Sliding Mode Tracking Control for High-speed Trains With Input Constraints and Parametric Uncertainties

Zikang Li,Deqing Huang,Liangcheng Cai 제어·로봇·시스템학회 2024 International Journal of Control, Automation, and Vol.22 No.3

In this paper, a finite-time tracking control strategy for high-speed trains (HSTs) subjected to inputconstraints and parameter uncertainties is proposed based on adaptive nonsingular terminal sliding mode control(ANTSMC), which achieves the fast and precise displacement-speed trajectory tracking and energy saving results. The dynamic model of HST is established with the basic, additional, and external disturbances firstly. To handle input constraints, a smooth hyperbolic function is designed to approximate saturation function, which guarantees thatthe control signal does not exceed traction/braking characteristics and ensures safe operation. Then, an adaptivemechanism is used to estimate the upper bounder of the lumped uncertainty and controller’s parameters. Subsequently, the proposed ANTSMC methodology not only assures the finite-time convergence of position and velocitytracking errors, but also effectively compensates parameter uncertainties of the proposed model. Finally, numerical simulations indicate that the proposed method spends the less traction energy in obtaining the better trackingperformance of HST.

An Open-switch Fault Diagnosis Method for Single-phase PWM Rectifier Based on CEEMD-DNN

Na Qin,Tianwei Wang,Deqing Huang,Yiming Zhang,Lei Ma 제어·로봇·시스템학회 2023 International Journal of Control, Automation, and Vol.21 No.10

Based on complementary ensemble empirical mode decomposition and deep neural network (CEEMDDNN), a novel diagnosis method is proposed to discover the open-circuit faults of insulated gate bipolar transistors (IGBTs) in single-phase pulse width modulation (PWM) AC-DC rectifier, an important part of traction power supply system of high-speed railway. By virtue of the combination of signal processing and deep learning schemes, the multi-scale feature information for IGBT’s open-circuit fault diagnosis are extracted by regarding the input current of rectifier as the original signal. More clearly, CEEMD is adopted to decompose the original signal to a series of intrinsic mode function components (IMFs). Then, the correlation coefficient algorithm is used to evaluate the correlation between each of the IMFs and the original signal. Further, those IMFs that have been verified to be highly correlated with the original signal are selected as the input eigenvectors of DNN to train the IGBTs fault diagnosis network. Experimental results show that the proposed CEEMD-DNN algorithm is superior to pure DNN, empirical mode decomposition (EMD)-DNN and ensemble empirical mode decomposition (EEMD)-DNN in the sense that within the similar time-consuming situations the fault diagnosis accuracy has been improved from 73.0%, 86.0%, and 89.9% to almost 99.0%. This is mainly owing to the remarkable decomposing performance of CEEMD for complex mixed signal, and the strong feature extraction and learning abilities of DNN in pattern recognition.

Sensor Fault Diagnosis and Unknown Disturbances Estimation of High Switching Frequency Single-phase PWM Rectifier

Habib Ullah Khan Jadoon,Deqing Huang,Na Qin,Zifeng Gong 제어·로봇·시스템학회 2021 International Journal of Control, Automation, and Vol.19 No.8

The fault and disturbances estimation has an important role in the modern traction railway system. This paper proposes a unique method for the real-time robust sensor fault detection and unknown bounded disturbances estimation of high switching frequency single-phase pulse width modulation (PWM) rectifier. The new state observer is designed for open-circuit sensors fault for single-phase PWM rectifier. The digital realization method is used to minimize the observer fluctuation in presence of fault with and without external disturbance. The fault diagnosis approach constitutes on threshold establishment with respect to residual generation based on observer and estimator. The impact of uncertainties is reduced and the convergence speed of fault estimation and accuracy is improved by H∞ performance level. The extensive simulations are implemented to validate the effectiveness of the proposed algorithm. From the presented results, the performance of the proposed method is illustrated along with the fault isolation and disturbance estimator.

An Iterative Learning Control Approach for Linear Time-invariant Systems with Randomly Varying Trial Lengths

Xuefang Li,Jian-Xin Xu,Deqing Huang 제어로봇시스템학회 2013 제어로봇시스템학회 국제학술대회 논문집 Vol.2013 No.10

This paper addresses an iterative learning control (ILC) design problem for discrete-time linear systems where the trial lengths could be randomly varying in the iteration domain. An ILC scheme with an iteration-average operator is introduced for tracking tasks with non-uniform trial lengths, which thus mitigates the requirement on classic ILC that all trial lengths must be identical. The learning convergence condition of ILC in mathematical expectation is derived through rigorous analysis. As a result, the proposed ILC scheme is applicable to more practical systems. In the end, an illustrative example is presented to demonstrate the performance and the effectiveness of the averaging ILC scheme.