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American control Conference

作者： Mengxiang Liu Chengcheng Zhao Ruilong Deng Peng Cheng Wenhai Wang Jiming Chen State Key Lab. of Industrial Control Technology Zhejiang University Hangzhou 310027 P. R. China School of Computer Science and Engineering Nanyang Tec

ISBN: (纸本)9781538679012;9781538679265

In this paper, we explore the potential stealthy attacks in the DC microgrid (DCmG) equipped with unknown input observer (UIO) based detectors, which are widely adopted for the detection and identification of cyber-attacks. We first prove that once the attacker knows the bounds of the initial state estimation error and the measurement noise, he/she can launch the nonzero-dynamics stealthy (NDS) attack in the DCmG, which can affect the detection residual while keep stealthy. Considering the complexity of the multi-layer control framework in the DCmG, we simplify the primary control loops as static unit gains and obtain the systematic dynamic model of the DCmG under the NDS attack. Then, we obtain the analytical expressions of the Point of Common Coupling (PCC) voltages, which are utilized to analyze the effects of the NDS attack on voltage balancing and current sharing, respectively. Moreover, we prove that under the NDS attack, the voltage and current convergence can still be achieved exponentially in the DCmG. Finally, extensive simulations are conducted in Simulink/PLECS to validate our theoretical results.

关键词： distributed control distributed power generation observers power generation control power system protection power system state estimation voltage control power system state estimation power generation control Power system protection distributed power generation diazonaphthalenedisulfonic acid decentralised control Voltage regulation Observers impact assessment voltage balance

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A Learning Evasive Email-Based P2P-Like Botnet

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China Communications 2018年第2期15卷 15-24页

作者： Zhi Wang Meilin Qin Mengqi Chen Chunfu Jia Yong Ma College of Computer and Control Engineering Nankai University Tianjin 300350 China Information Security Evaluation Center of Civil Aviation Civil Aviation University of China Tianjin 300300 China Key Lab. on High Trusted Information System in Hebei Province Baoding 071002 China

Nowadays, machine learning is widely used in malware detection system as a core component. The machine learning algorithm is designed under the assumption that all datasets follow the same underlying data distribution. But the real-world malware data distribution is not stable and changes with time. By exploiting the knowledge of the machine learning algorithm and malware data concept drift problem, we show a novel learning evasive botnet architecture and a stealthy and secure C&C mechanism. Based on the email communication channel, we construct a stealthy email-based P2 P-like botnet that exploit the excellent reputation of email servers and a huge amount of benign email communication in the same channel. The experiment results show horizontal correlation learning algorithm is difficult to separate malicious email traffic from normal email traffic based on the volume features and time-related features with enough confidence. We discuss the malware data concept drift and possible defense strategies.

关键词： malware botnet learning evasion command and control

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Fuzzy Q-learning obstacle avoidance algorithm of humanoid robot in unknown environment

Fuzzy Q-learning obstacle avoidance algorithm of humanoid ro...

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第37届中国控制会议

作者： Shuhuan Wen Jianhua Chen Zhen Li Ahmad B.Rad Kamal Mohammed Othman the Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University the school of Engineering Sciences Simon Fraser University

This paper proposes a fuzzy Q-learning(FQL)algorithm to solve the problem of the robot obstacle avoidance in unknown *** algorithm is used to localize the position of the *** Q-learning algorithm,optimized Q-learning algorithm,FQL algorithm are *** simulation results show that FQL algorithm has a faster learning speed than other two algorithms and the results demonstrate that the fuzzy Q-learning obstacle avoidance algorithm is effective.

关键词： FASTSLAM fuzzy logic control path planning obstacle avoidance Q-learning

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Research on Position Synchronization System control of Internal High Pressure Forming Machine Based on WinCC

Research on Position Synchronization System Control of Inter...

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第30届中国控制与决策会议

作者： Zhaoyuan Jiang Lixin Wang Jiaqiu Song Fucai Liu Key Laboratory of Industrial Computer Control Engineering of Hebei Province Yanshan University Yanshan University Engineering Training Center

Both sides of the level hydraulic cylinder on internal high pressure forming machine position synchronous system control is one of the key technologies for Internal high pressure forming system, control performance directly affects the production efficiency and product *** on this problem,multivariate coordinated control simulation test platform is be seted up. Mainly includes the control scheme design, control system hardware and software design. The Siemens S7-300 PLC has been as the main controller,WinCC as the upper computer software. Finally based on FM355 C module position synchronization control experiment was carried out by the PID algorithm. the experiment result shows that, in the slope under the condition of smaller FM355 C position synchronization control effect is good, the system can meet the production requirements of internal high pressure forming.

关键词： Paper Internal high pressure forming WinCCSynchronous control S7-300

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Research and Application of Flatness control for Tandem Cold Rolling

Research and Application of Flatness Control for Tandem Cold...

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第37届中国控制会议

作者： LI Xiaogang FANG Yiming LIU Le Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University National Engineering Research Center for Equipment and Technology of Cold Strip Rolling

Compound wave defect occurs in flatness during tandem cold rolling when high-end automobile and household appliance plate are produced, which has several impact on line speed and quality of final product. In this paper, a further research is done on sourcing cause of formation for the flatness defect. In combination with adjusting actuators and automatic flatness control principles, Achieving target flatness by rolls tilting, work rolls bending, middle rolls bending, and section cooling *** control output of tilting, work rolls and middle rolls bending are calculated by the least square method. Section cooling control output of rolling is calculated by the typical fuzzy control theory. The least square method and fuzzy control algorithm are optimized so as to enhance control accuracy of automatic flatness, and at the same time largely improve flatness of steel strip, reduce working strength of operators and improve production efficiency of production line.

关键词： Tandem cold rolling Automatic flatness control Least square method Fuzzy control

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Fuzzy Q-learning obstacle avoidance algorithm of humanoid robot in unknown environment

Fuzzy Q-learning obstacle avoidance algorithm of humanoid ro...

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Chinese control Conference

作者： Shuhuan Wen Jianhua Chen Zhen Li Ahmad B. Rad Kamal Mohammed Othman Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao China School of Engineering Sciences Simon Fraser University Surrey BC Canada

This paper proposes a fuzzy Q-learning (FQL) algorithm to solve the problem of the robot obstacle avoidance in unknown environment. FastSLAM algorithm is used to localize the position of the robot. Traditional Q-learning algorithm, optimized Q-learning algorithm, FQL algorithm are compared. The simulation results show that FQL algorithm has a faster learning speed than other two algorithms and the results demonstrate that the fuzzy Q-learning obstacle avoidance algorithm is effective.

关键词： Collision avoidance Path planning Convergence Humanoid robots Mobile robots Fuzzy sets

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An Ameliorated Moth-flame Optimization Algorithm

An Ameliorated Moth-flame Optimization Algorithm

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第37届中国控制会议

作者： Xiao-dong Zhao Yi-ming Fang Zhuang Ma Miao Xu Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University National Engineering Research Center for Equipment and Technology of Cold Strip Rolling Tangshan University

To improve the global search ability under the condition of ensuring convergence speed, it is still a major challenge for most meta-heuristic optimization algorithms. The Moth-Flame Optimization（MFO） algorithm is an innovative nature-inspired algorithm. To improve the precision of the solution and to quicken the convergence speed and to increase the stability of MFO,an ameliorated Moth-flame optimization algorithm（A-MFO） that combines the crisscross optimization algorithm with MFO is proposed to solve this problems that are mentioned above. The performance of proposed A-MFO is demonstrated on six benchmark mathematical function optimization problems regarding superior accuracy and lower computational time achieved compared to other well-known nature-inspired algorithms.

关键词： Moth-flame optimization algorithm crisscross optimization algorithm stochastic optimization convergence

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Electrochemical Detection of Insulin Based on Screen Printed Electrode Modified by Nickel Hydroxide

Electrochemical Detection of Insulin Based on Screen Printed...

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International Conference on Micro/Nano Sensors for AI, Healthcare, and Robotics (NSENS)

作者： Hongyu Zhang Zhikun Zhan Yuliang Zhao Xiaopeng Sha Xiaodong Yu Hui Sun Lijia Gu Jiali Liu Lianqing Liu Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao China School of Control Engineering Northeastern University at Qinhuangdao Qinhuangdao China State key Laboratory of Robotics Chinese Academy of Sciences

ISBN: (纸本)9781538694091;9781538694084

This paper reports a novel electrochemical method for the detection of insulin in ultra-pure water. A screen printed electrode (SPE) modified by Nickel hydroxide was used as the working electrode, one with good activity of electro-catalytic oxidation-reduction for insulin. The SPE was modified by Nickel hydroxide using the electrodeposition method. The results showed that Nickel hydroxide was homogeneously electrodeposited on the surface of the working electrode. A coin-size electrolytic tank was fabricated with PDMS, which only requires 0.3ml of sample for the detection. The concentration of insulin was analyzed using the methods of Cyclic voltammetry (CV), Electrochemical impedance spectroscopy (EIS) and Chronoamperometry (i-t). The Nickel hydroxide used for detecting insulin showed good analytical characteristics, such as a high sensitivity of 14.797μA·μM -1 , a good linear detection range of 100nM-5μM, and a low detection limit of 93nM. This nickel hydroxide modified SPE electrode has a much smaller size and is easier to fabricate than traditional electrodes, making it a much more promising candidate for an insulin sensor.

关键词： Electrodes Insulin Nickel Oxidation Sensitivity Surface treatment Diabetes

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Looseness Detection of Rail Fasteners Using MEMS Sensor and Power Spectrum Entropy

Looseness Detection of Rail Fasteners Using MEMS Sensor and ...

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International Conference on Micro/Nano Sensors for AI, Healthcare, and Robotics (NSENS)

作者： Hao Sun Zhikun Zhan Hongyu Zhang Junshan Liu Xiaopeng Sha Xiaodong Yu Jianing Yu Yuliang Zhao Lianqing Liu Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao China School of Control Engineering Northeastern University at Qinhuangdao Qinhuangdao China State key Laboratory of Robotics Chinese Academy of Sciences

ISBN: (纸本)9781538694091;9781538694084

Rail fasteners, a key component of a railway track, are used to connect the rail and the sub-rail foundation together with the required degree of elasticity. Severely loose or failed fasteners may lead to serious safety hazards for rail transportation. However, current strategies for determining fastener looseness are mainly implemented manually, which is labor-intensive, inefficient and less-than-objective. In this paper, we propose a system that uses a MEMS acceleration meter and a wireless data transmission technique to detect railway fasteners. Vibration was generated by hitting the rail with a hammer. Then the acceleration data was transmitted to the cloud by the Global System for Mobile Communications (GSM) technique. The fastener looseness was analyzed using power spectrum entropy and frequency domain analysis. Results from the field experiments show that our method can identify the fastener's loosening state accurately and automatically. This wireless, low-cost fastener inspection system is expected to provide an effective approach to improving the efficiency of regular railway maintenance..

关键词： Conferences Artificial intelligence Medical services Robot sensing systems IP networks

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Flatness predictive model based on T-S cloud reasoning network implemented by DSP

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Journal of Central South University 2017年第10期24卷 2222-2230页

作者： ZHANG Xiu-ling GAO Wu-yang LAI Yong-jin CHENG Yan-tao Key Laboratory of Industrial Computer Control Engineering of Hebei Province Yanshan UniversityQinhuangdao 066004China National Engineering Research Center for Equipment and Technology of Cold Strip Rolling Yanshan UniversityQinhuangdao 066004China

The accuracy of present flatness predictive method is limited and it just belongs to software simulation. In order to improve it, a novel flatness predictive model via T-S cloud reasoning network implemented by digital signal processor(DSP) is proposed. First, the combination of genetic algorithm(GA) and simulated annealing algorithm(SAA) is put forward, called GA-SA algorithm, which can make full use of the global search ability of GA and local search ability of SA. Later, based on T-S cloud reasoning neural network, flatness predictive model is designed in DSP. And it is applied to 900 HC reversible cold rolling mill. Experimental results demonstrate that the flatness predictive model via T-S cloud reasoning network can run on the hardware DSP TMS320 F2812 with high accuracy and robustness by using GA-SA algorithm to optimize the model parameter.

关键词： T-S cloud reasoning neural network cloud model flatness predictive model hardware implementation digital signal processor genetic algorithm and simulated annealing algorithm (GA-SA)

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