Huang Zhiwu
Central South University
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Publication
Featured researches published by Huang Zhiwu.
chinese control conference | 2006
Huang Zhiwu; Shan Yongteng; Gui Weihua; Nian Xiao-hong
By analyzing the existence of unstable regions of the present adaptive observer using pole-placement technique in regenerating mode at low speeds, conditions that ensure the adaptive observer stability at full speed regions are got. An improved speed adaptive law and a novel method to choose the gain of the observer are proposed based on observer. By using the Lyapunov stability theory, speed identification adaptive law is got. The gain of the observer can be obtained by solving two bilinear matrix inequalities. The simulation model of speed sensorless induction motor using direct torque control based on observer is built in the Matlab/Simulink. Simulation results show that the adaptive observer has good steady and dynamic performances and good robustness.
world congress on intelligent control and automation | 2008
Huang Zhiwu; Zhou Sheng; Gui Weihua; Liu Jianfeng
Multifunction vehicle bus (MVB) is a standard protocol defined in train communication network criterion, and used for transmitting information among various equipments inside the vehicle. In order to insure compatibility and inter-operability among the MVB equipment, it requires that the data transmitted in the bus need to be collected, and correctness and reliability of data transmission of the MVB network should be analyzed. Base on the characters of periodically broadcasting and master slave frame response. According to IEC61375 standard, this paper proposes a method to implement an analyzer for MVB device protocol. In the method, the transmitted data on the bus are sampled using error-tolerance decode algorithm, and then the compatibility and dependability of data transmission among devices are analyzed via protocol analysis application. The experiment results showed that the analyzer can exactly validate the design of the equipment on the MVB bus.
ieee international conference on computer science and information technology | 2009
Yang Yingze; Gui Weihua; Huang Zhiwu
In view of that Sync brake system of combined-train has a complex configuration and distributed control characteristic, an on-line diagnosis system based on multi-agent technique is designed. The diagnosis system is a two-level multi-agent system, in which diagnosis tasks are divided into simple tasks and accomplished by agents with collaboration. Based on the design of the diagnosis system, the key problems such as the mechanism of task decomposition as well as agent collaboration are resolved. The application results show the validity of this diagnosis method.
ieee international conference on communication software and networks | 2011
Peng Jun; Li Zheqin; Jiang Fu; Ma Jianjiang; Huang Zhiwu
The wireless mesh network (WMN) has recently emerged as a promising technology for distributed wireless networking. In multi-radio multi-channel heterogeneous WMNs, load balancing can avoid congestion thus to improve the overall performance. A cross-layer cognitive routing protocol with load balance which using RACIM, a new metric, to choose qualified routing paths is presented. RACIM can evaluate the link quality and load status by incorporating the cross-layer cognitive information, such as channel bandwidth, the rate of transmission bit error (BER) and the frequency of channel etc. In order to share cognitive information between layers, we add a new type of ICMP message. The simulation results show the effectiveness of the proposed protocol.
chinese control conference | 2006
Liu Jianfeng; Gui Weihua; Huang Zhiwu
A T-S model fuzzy modeling method based on satisfying degree function is presented for a class of complex systems. Using the sampling data, the model parameters are initialized by fuzzy clustering and its premise parameters are rectified by learning off-line using back-propagation algorithm. Introducing the conception of character satisfying degree function to rectify online the forgetting factor of recursive least square method, the consequent parameters of the fuzzy rules are self-learning online by recursive least square method. Consequently, the precision and the identify speed of the T-S model are improved. Applying to locomotive brake control unit, the result shows the effectiveness of the proposed method.
international conference on transportation mechanical and electrical engineering | 2011
Yang Yingze; Huang Zhiwu; Li Shuo; Zhang Tao
To solve pneumatic pipe leakage of freight train, a base flow detection algorithm is proposed. Firstly principle of pneumatic brake system is analysed, workflow and fault characteristics of pneumatic pipe leakage are researched. Then detection process of pneumatic pipe leakage is designed with maintenance requirement. At last a base flow leakage diagnosis algorithm is discussed and verified. Experiment datas indicate this diagnosis technology ensure the dynamic operating conditions and security of the algorithm reliability with stability.
chinese control conference | 2006
Huang Zhiwu; Yang Tongguang; Gui Weihua; Shan Yongteng; Nian Xiao-hong
Speed identification is crucial in speed sensorless induction motor drives. Because the voltage model involves pure integrator, which will cause initial value and drift problems. These problems and resistance varies effect the precision of speed identification. This paper presents an improved method, which uses high-pass filter to avoid these problems and adapt the cut-off frequency on-line to improve dynamic performance by using fuzzy controller; and then eliminate the influence of stator resistance varies by using fuzzy controller to estimate and adapt stator resistance on-line. Simulation results indicate that the method has the characteristic of good dynamic and static performance and high precision speed identification.
Archive | 2014
Yang Yingze; Li Shuo; Huang Zhiwu; Gao Kai; Zhang Xiaoyong; Jiang Fu; Peng Jun; Liu Weirong
Archive | 2014
Huang Zhiwu; Liu Weirong; Li Shuo; Zhang Xiaoyong; Peng Jun; Jiang Fu; Yang Yingze; Gao Kai
Archive | 2014
Peng Jun; Yang Yingze; Huang Zhiwu; Zhang Xiaoyong; Jiang Fu; Li Shuo; Gao Kai; Yu Wentao; Zhu Zhengfa