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( Xianwen He ),( Gaoqi Dou ),( Jun Gao ) 한국인터넷정보학회 2018 KSII Transactions on Internet and Information Syst Vol.12 No.8
In this paper, we investigate an individual channel estimation problem for multiple-input multiple-output (MIMO) two-way amplify-and-forward (AF) relay networks. To avoid self-interference during the estimation of the individual MIMO channels, a novel blind interference cancellation (BIC) approach is proposed based on an orthogonal preceding framework, where a pair of orthogonal precoding matrices is utilized at the source nodes. By designing an optimal decoding scheme, we propose to decompose the bidirectional transmission into a pair of unidirectional transmissions. Unlike most existing approaches, we make the practical assumption that the nonreciprocal MIMO channel and the mutual interference of multiple antennas are both taken into consideration. Under the precoding framework, we employ an orthogonal superimposed training strategy to obtain the individual MIMO channels. However, the AF strategy causes the noise at the terminal to be the sum of the local noise and the relay-propagated noise. To remove the relay-propagated noise during the estimation of the second-hop channel, a partial noise-nulling method is designed. We also derive a closed-form expression for the total mean square error (MSE) of the MIMO channel from which we compute the optimal power allocation. The simulation results demonstrate that the analytical and simulated curves match fully.
Lian Lian,Xianwen Gao,Wenhai Qi 제어·로봇·시스템학회 2016 International Journal of Control, Automation, and Vol.14 No.3
The paper is concerned with the problem of H∞ control for stochastic time-delayed Markovian switchingsystems with partly known transition rates and input saturation. By employing more appropriate Lyapunov-Krasovskii functional, a state feedback controller is designed to guarantee stochastic stability of the correspondingclosed-loop system with H∞ performance. A linear matrix inequality approach is employed to obtain the controllergain matrix. Two illustrative examples are provided to show the potential of the proposed techniques.
L1 Control for Positive Markovian Jump Systems with Partly Known Transition Rates
Wenhai Qi,Xianwen Gao 제어·로봇·시스템학회 2017 International Journal of Control, Automation, and Vol.15 No.1
This paper deals with the problem of L1 control for positive Markovian jump systems with partly knowntransition rates. First, by constructing an appropriate linear co-positive type Lyapunov-Krasovskii function, stochasticstability for the underlying system is discussed. Then, the L1-gain performance is analyzed. Based on the resultsobtained, an effective method is proposed for the design of state feedback controller. All the proposed conditionsare derived to ensure that the closed-loop Markovian jump system positive and stochastically stable with L1-gainperformance in linear programming. Finally, an example is given to demonstrate the validity of the main results.
Wenhai Qi,Xianwen Gao 제어·로봇·시스템학회 2016 International Journal of Control, Automation, and Vol.14 No.6
The paper is concerned with the problem of positive L1-gain filter design for positive continuous-timeMarkovian jump systems with partly known transition rates. Our aim is to design a positive full-order filter such thatthe corresponding filtering error system is positive and stochastically stable with L1-gain performance. By applyinga linear co-positive Lyapunov function and free-connection weighting vectors, the desired positive L1-gain filter isprovided. The obtained theoretical results are demonstrated by numerical examples.
Dezhi Hao,Xianwen Gao,Wenhai Qi 제어·로봇·시스템학회 2022 International Journal of Control, Automation, and Vol.20 No.11
In this paper, a novel data augmentation method is proposed for imbalanced fault diagnosis in the sucker rod pumping system (SRPS) based on the improved generative adversarial network (GAN). The dynamometer cards (DCs) of minority fault classes are expanded steadily through learning the data distribution of the original imbalanced training data. The generalization ability and accuracy of the different fault diagnosis models are improved with the expanded DCs. Firstly, benefit from introducing the auxiliary conditional information to the Wasserstein GAN with gradient penalty (WGAN-GP), a stable and practical framework is constructed to generate specific categories of DCs. Secondly, the traditional random noise is replaced by the Gaussian mixture noise to guarantee the diversity of the generated DCs with few training samples. Moreover, problematic training, such as unstable training and mode collapse, is effectively avoided with the presented optimization strategy, training structure and data processing method. Eventually, generated data evaluation and comparative experiments are conducted using practical DCs collected from several oil wells with similar working conditions in the northeastern of China. The results verify the validity of the proposed data augmentation method.
Jiyang Wang,Wenhai Qi,Xianwen Gao,Yonggui Kao 제어·로봇·시스템학회 2017 International Journal of Control, Automation, and Vol.15 No.2
The paper is concerned with positive observer design for positive Markovian jump systems with incompletetransition rates and time delays that are mode-dependent and time-varying. Firstly, by applying an appropriateco-positive type Lyapunov-Krasovskii function and free-connection weighting vectors, sufficient conditions areproposed to ensure stochastic stability of the error positive system and existence of the positive observer. All theproposed conditions are derived in linear programming. Finally, an example is given to demonstrate the validity ofthe main results.
Wenhai Qi,Yonggui Kao,Xianwen Gao 제어·로봇·시스템학회 2017 International Journal of Control, Automation, and Vol.15 No.5
The paper deals with the problems of passivity and passification for stochastic systems with Markovianswitching and generally uncertain transition rates. The considered systems are more general, which cover uncertaintransition rates and partly known transition rates as two special cases. By employing the multiple Lyapunov functionand some free-weighting matrices, a state feedback controller is constructed such that the resulted closed-loopsystem is stochastically passive. Some sufficient conditions for the solution to the problem are derived in the formof linear matrix inequalities (LMIs). Finally, a numerical example is given to demonstrate the validity of the mainresults.
New Results on Finite-time Stabilization for Stochastic Systems with Time-varying Delay
Lihua Zhang,Wenhai Qi,Yonggui Kao,Xianwen Gao,Longjiang Zhao 제어·로봇·시스템학회 2018 International Journal of Control, Automation, and Vol.16 No.2
The paper deals with the problem of finite-time stabilization for stochastic systems with time-varying delay by defining a new criterion for finite-time stability. Firstly, by use of more appropriate Lyapunov-Krasovskii functional (LKF), the difficulties of finite-time stability confronted in system analysis and synthesis can be overcome. Then, a state feedback controller is constructed to guarantee the closed-loop system finite-time stable. New conditions for finite-time stability analysis as well as controller synthesis are established in terms of linear matrix inequality (LMI). Finally, two practical examples demonstrate the validity of the main results.
Zhengxuan Jiang,Kun Liang,Xiang Gao,Fan Cao,Guangqi An,Siyu Gui,Weiwei Tang,Liping Du,Liming Tao,Xianwen Wang 한국생체재료학회 2023 생체재료학회지 Vol.27 No.00
Background EAU is an inflammatory disease usually characterized by autoinflammation and autoimmunity and is aggravated by excessive generation of ROS. Conventional hormone therapy often has more adverse effects. It is urgent to find a therapeutic drug with higher efficiency and fewer adverse effects. Methods We developed an Fe-curcumin nanozyme in which natural antioxidants coordinate with Fe3+ to form nanoparticles with excellent solubility for directing anti-inflammatory and ROS scavenging effects to treat EAU. Several experiments were used to detect the characteristics of nanozymes. EAU model rats were used to detect the abilities of decreasing autoinflammation and autoimmunity. PBMCs were used to detect the ability to inhibit cell proliferation. Results Free radical scavenging experiments showed that nanozymes decreased the level of free radicals at low concentrations. In vitro and in vivo experiments revealed that the group treated with Fe-curcumin nanozymes had lower inflammatory reactions and ROS levels than the control group, as reflected by the downregulated levels of several critical inflammatory cytokines, such as IFN-γ, IL-17, and TNF-α; decreased H2O2 release; inhibited proliferation of Th1 and Th17 cells; and alleviated pathological changes in the eye. Importantly, the Fe-curcumin nanozyme was detected in the retina using Prussian blue staining. Additionally, Fe-curcumin nanozyme is noncytotoxic when directing these biological activities. Conclusion This study has demonstrated the feasibility of using the Fe-curcumin nanozyme as a nanodrug to inhibit inflammatory reactions and scavenge ROS in the treatment of EAU, indicating that it may serve as a promising therapeutic agent in clinical treatment.
Stochastic Stability, ℒ1-gain and Control Synthesis for Positive Semi-Markov Jump Systems
Longjiang Zhao,Wenhai Qi,Lihua Zhang,Yonggui Kao,Xianwen Gao 제어·로봇·시스템학회 2018 International Journal of Control, Automation, and Vol.16 No.5
This paper treats the problems of stochastic stability, ℒ1-gain and control synthesis for positive semi- Markov jump systems (S-MJSs). The system under consideration involves semi-Markov stochastic process related to Weibull distribution. The main motivation for this paper is that the positive condition sometimes needs to be considered in S-MJSs and the controller design methods in the existing works have some conservation. To deal with these problems, some sufficient conditions for stochastic stability of positive S-MJSs are established by implying the linear co-positive Lyapunov function. Then, some sufficient conditions for ℒ1-gain constraint are also presented, upon which, a state feedback controller is designed by decomposing the controller gain matrix such that the resulting closed-loop system is positive and stochastically stable with ℒ1-gain performance in the form of standard linear programming (LP). The advantages of the new framework lie in the following facts: (1) the weak infinitesimal operator is derived for S-MJSs under the constraint of positive condition and (2) the less conservative stabilizing controller is designed to achieve the desired control performance. Finally, numerical examples are given to demonstrate the validity of the main results.