Zeng Deliang

Consensus of second-order multi-agent systems with nonuniform time delays

In this study, the consensus problem for a class of second-order multi-agent systems with nonuniform time delays is investigated. A linear consensus protocol is used to make all agents reach consensus and move with a constant velocity. By a frequency-domain analysis, a simplified sufficient condition is given to guarantee the consensus stability of the dynamic system. Finally, the effectiveness of the obtained theoretical results is illustrated through numerical simulations.

Identification of a boiler-turbine system using T-S fuzzy model

This paper discusses a model identification method using T-S fuzzy model. And the fuzzy entropy is defined and on-line identification algorithm based on maximum fuzzy entropy and loss function is proposed. Using the identification algorithm, we get the high precision local linear model of a boiler-turbine fuzzy model. And this provides the basement of a new way to control the complex nonlinear system using the traditional control strategy.

H∞ consensus control of a class of second-order multi-agent systems without relative velocity measurement

This paper studies consensus control problems for a class of second-order multi-agent systems without relative velocity measurement. Some dynamic neighbour-based rules are adopted for the agents in the presence of external disturbances. A sufficient condition is derived to make all agents achieve consensus while satisfying desired H∞ performance. Finally, numerical simulations are provided to show the effectiveness of our theoretical results.

Control-decision and integrated information system of power plant

This paper introduces the structure of the integrated information system of the power plant. This system can be classified by two components, one is the integration of the control and diagnostic system, the other is integration of the management information and real-time information. Multi-goal optimization and coordination can be used to realize the integration of the control systems, and failure trend-based forecasting methods can be used to realize the integration between the control and diagnostic systems. Through the inter-link between the distributed control system (DCS) networks, the information can be shared by real-time system and management system.

Data-driven state detection algorithm for multi-scale systems and its application

To improve the security and reliability of equipment and reduce their failure rate, a data-driven state detection algorithm was proposed. The concepts of multi-scale system, multi-scale entropy and multi-scale exergy were defined. The algorithm is used for multi-scale systems whose state parameters change over time and have the characteristic of increasing monotonically on a dominant scale. An abrasion index for the middle speed roller ring mill was constructed, which was used to monitor the states of the instruments. Noise that affected the accuracy of the results was analyzed. The results of simulation experiments demonstrate the effectiveness of the algorithm, which can provide a technical basis for condition maintenance.

Model identification of coal mill control system based on genetic algorithm

This paper is based on the experimental data of the coal mill control system of the full incentive simulator. The two — point method and the genetic algorithm are used to identify the experimental results. The results are compared with each other, and the transfer function is obtained. The study of the coal mill control system model is the basis for analyzing the boiler combustion control system, establish a precise coal mill control system model, can further enhance the boiler combustion efficiency and economic benefits, and better protection of the safe operation of the boiler unit.

Modeling and simulation of indoor environment parameters based on least squares

Indoor building environment for energy saving and human health has important significance and the main criterion for evaluating its quality is environmental comfort. An experimental scheme for obtaining the mathematical model of the main parameters is designed by analyzing the parameters that affect the environmental comfort. The scheme establishes a discrete bilinear model with parameters and control variables, and uses the the least squares method to obtain the model parameters based on the experimental data. The simulation results show that the experimental scheme of this paper has strong universality and adaptability, and the model with the deviation of the real system is small, which can be used as the model basis for optimizing the control of the indoor building environment.

An automatic control method of heat extraction system in thermal power unit

Affected by the operation mode of “ordering power by heat”, the peak regulation shortage of combined heat and power (CHP) units in north China limits the absorption of renewable energy. To solve this problem, the improvement of heat steam extraction system control performance is essential. An automatic control method of heat extraction system is presented. The regulation of heat steam flow is realized by periodic execute pulse, and an open-loop control strategy is designed to regulate the supply water temperature of heating network. The renovation is applied to a 330MW CHP unit. The result shows the safe and reliable use of the heat steam extraction system control method, which lays the foundation of peak regulation study of CHP unit based on heat network energy storage.

Audio data compression based on AVS-P10

AVS-P10 is the first national standard for mobile audio codec with completely independent intellectual property rights. In view of the current situation of the explosive growth of network audio data, According to the principle of AVS-P10 coding and based on AVS-P10 core encoder to make the algorithm compile. And the algorithm is optimized by the self search cycle optimization scheme. Finally, the third National Graduate smart city technology and creative design contest organized by the audio data to do the experiment. And the experimental results show that the algorithm has achieved some results. At the same time, the compression ratio of the optimized algorithm increases with the same code rate.

Data driven state detection algorithm for ash deposition detection

A data driven state detection algorithm was proposed to improve the security and reliability of equipment. The algorithm is used for one class of objects whose state parameters change slowly and cumulatively in the long term. The concepts of multi-scale system, multi-scale entropy and multi-scale exergy were used to describe these processes. With the help of the algorithm, an ash deposition index for the radiant heating surface of a 600 MW unit was constructed to monitor the states of the instruments. Noise was analyzed. The results of simulation experiments demonstrate the effectiveness of the algorithm, which can provide a technical basis for condition maintenance.