МЕТОДОЛОГИЧЕСКИЕ ОСНОВЫ РАЗРАБОТКИ ИНТЕЛЛЕКТУАЛЬНЫХ СИСТЕМ УПРАВЛЕНИЯ УПЛОТНЕНИЕМ АСФАЛЬТОБЕТОННЫХ СМЕСЕЙ

Ensemble of long short-term memory prediction and variable universe fuzzy control for seismic response reduction using electromagnetic dynamic vibration absorber

Обоснован перечень задач самообучения интеллектуальных систем управления автономными роботами и мультиагентными робототехническими группировками. Обсуждаются основные проблемы создания интеллектуальных самообучающихся систем управления. Показано, что один из наиболее перспективных подходов к реализации процессов самообучения в интеллектуальных системах управления автономными роботами и многоагентными робототехническими группировками связан с использованием метода автоматического построения деревьев классификации. Приводятся результаты комплексного моделирования.

With the progress of computer technology and intelligent control system, it is necessary to introduce the PLC together with the current systems. In this paper, we conduct research on the new intelligent industrial control and communication system based on PLC technique. As Industry 4.0 at the core of intelligent factory, the products made in its basic idea is integrated with dynamic digital memory, perception and communication ability, carrying the whole supply chain and all kinds of information required for life cycle. PLC biggest characteristic is to constitute the traditional relay model computer software technology, formed a unique style in relay ladder graph based image programming language, the PLC control system in the form of program to achieve its control function. In the simulation section, we implement our proposed system in detail and conduct numerical analtsis and simulation. The result is acceptable and accurate.

Based on heat balance analysis, the dynamic heating model of asphalt tank of mixture equipment was established, the heating time and using time nodes were determined, and the trapezoidal dynamic heating process of asphalt tank was also formed to realize the intelligent control and reduce energy consumption. After analyzing different schemes, the control scheme of the combination of feed-forward and feedback to realize intelligent control system for asphalt tank was adopted, which could ensure that the asphalt in the tank is in the operating temperature and the mixing equipment works continuously when the asphalt was used completely. In addition, a simulated analysis of calculation model, which was adopted by intelligent control system, was made in combination of entitative engineering. Results showed that compared with traditional process of heating asphalt, this intelligent heating control system could reduce the heat consumption by 15.8% under the condition of continuous construction.

With the development of network communication, computer technology and artificial intelligence, it has become an inevitable development trend to promote "intelligent buildings" characterized by intelligence, comfort and safety. In order to solve the shortcomings of the existing research on intelligent building control system, this paper discusses the functional equation of CAN algorithm, artificial intelligence fuzzy controller and intelligent building, and aims at the intelligent building control system based on artificial intelligence and CAN algorithm. Hardware settings and parameter settings are briefly introduced. And the work flow design of the intelligent building control system structure based on artificial intelligence and CAN algorithm is discussed, and finally the application of the intelligent building control system based on artificial intelligence and CAN algorithm is experimentally tested. The correct number of switch control by artificial intelligence and CAN algorithm in the intelligent building control system is relatively high. The correct number of switch control in the interference environment is less than that in the humid environment, and the number of switch operations for the control system is the least in the humid environment. The error rate of 500 and up to 2500 is less than 5%, thus verifying the superiority of the application of intelligent building control system based on artificial intelligence and CAN algorithm.

The main problem faced in supplying power to remote consumers is that there are high logistical costs of delivering fuel and equipment for diesel power plants, poor density of transport infrastructure and, as a consequence, a high cost of fuel. There are also high operating costs at diesel power plants and specific fuel consumption; in addition, there is no monitoring and control automation. In view of a high wind potential of the Arctic territories, energy complexes and systems can be effectively modernized and constructed on the basis of modular wind-diesel power plants with an intelligent control system. A concept of and hardware solutions for an intelligent automatic control system are proposed, the use of which makes it possible to maximize the amount of electricity generated by renewable sources owing to dynamically redistributing the power between the hybrid energy complex components and, as a result, to minimize fuel consumption. An analysis of a controlled wind-diesel power plant has shown that by using an intelligent automatic control system, forecasting the electricity generation by a wind power plant, and arranging storage battery operation in a cyclic mode, it becomes possible to effectively cover the load schedule of an autonomous consumer and increase the extent of diesel fuel substitution by up to 60 % or more.

This paper aims to present an implementation of advanced lighting control system in airport terminal. The lighting requirements of the terminal are fulfilled and regulated by an intelligent control system deployed with i-bus. The intelligent control system adjusts the lighting in terminal at different time according to the real-time requirements. Compared with conventional control system, this intelligent control system can control the lighting in time as long as the real-time requirements are shifted in a remote way. Besides, this new system can also save energy to a great extent.

Lighting system control techniques in commercial buildings: Current trends and future directions

During road construction, the accuracy of compaction work is critical for the structural stability and maintenance of the road. Although the plate load test (PLT) is commonly used for quality inspections, it is impractical to test every section due to time and cost constraints. Therefore, simpler testing methods are being extensively developed. This study compared quality inspection results using the commonly used PLT, the relatively simple dynamic cone penetrometer test (DCPT), the lightweight deflectometer (LWD) test, and an intelligent quality control system equipped with accelerometer and global positioning system (GPS) sensors in intelligent compaction (IC) rollers. The results showed a strong correlation between the conventional tests (PLT, DCPT, and LWD) and the values obtained from the intelligent quality control system. The correlation analysis between the intelligent quality control system and PLT, LWDT, and DCPT yielded R-square values of 0.69, 0.91, and 0.95, respectively, indicating significantly high correlations. The implementation of intelligent quality management systems in earthwork construction projects will facilitate a thorough verification of the compaction quality throughout all construction segments, ensuring consistent compaction across the project. By enabling real-time data acquisition and analysis, these systems differ markedly from traditional methods, reducing the frequency and necessity of manual inspections. This approach not only streamlines construction processes, but also enhances operational efficiency. As a result, integrating these intelligent systems is anticipated to significantly increase productivity by optimizing the workflow and resource utilization in earthwork construction.

This report presents a generalized design strategy of intelligent robust control systems based on quantum/soft computing technologies that enhance robustness of fuzzy controllers by supplying a self-organizing capability. It is demonstrated that fuzzy controllers prepared to maintain control object in the prescribed conditions are often fail to control when such a conditions are dramatically changed. We propose the solution of such kind of problems by introducing a generalization of strategies in fuzzy inference from a set of pre-defined fuzzy controllers by new quantum fuzzy inference based systems (prototype of intelligent system of systems engineering). We stress our attention on the robustness features of intelligent control systems.

An adaptive controller is proposed using a novel interval type-2 fuzzy cerebellar model articulation controller (T2FCMAC). The T2FCMAC realizes an interval type-2 fuzzy logic system based on the structure of the cerebellar model articulation controller (CMAC). Due to the better ability of handling uncertainties provided by type-2 fuzzy sets, it can solve some complicated problems with outstanding effectiveness than type-1 fuzzy sets. In addition, an intelligent control system is proposed; this control system is comprised of a T2FCMAC and an auxiliary compensation controller. The T2FCMAC is utilized to approximate a perfect controller and the parameters of T2FCMAC are on-line tuned by the derived adaptive laws based on a Lyapunov function. The auxiliary compensation controller is designed to suppress the influence of residual approximation error between the perfect controller and the T2FCMAC. Finally, a Chua's chaotic circuit is performed to verify the effectiveness of the proposed control scheme. The simulation results confirm that the proposed intelligent adaptive control system can achieve favorable tracking performance.

Revolutionizing gear hobbing machine precision: Innovative thermal error compensation and intelligent error control with enhanced crystal structure algorithm and self-attention bidirectional minimal gated unit network

Objective To investigate the clinical effectiveness of an intelligent shell temperature control system in deep tumor hyperthermia for controlling the temperature in the outer shell of chest and abdominal malignancies. Methods From 2015 to 2016, a randomized comparative study was carried out in the intelligent temperature control system (experimental group containing 37 patients with chest tumor and 26 patients with abdominal tumor) and conventional cooling by replacement of water bags (control group containing 37 patients with chest tumor and 25 patients with abdominal tumor) for chest and abdominal tumor hyperthermia. The effectiveness in controlling the outer shell temperature was compared between the two methods. Results In the experimental group, the first boot of the cooling system occurred at 24.1 and 21.8 minutes on average after the hyperthermia started and the average number of system boots was 2.5. In the control group, patients reminded to replace the water bag at 33.1 and 33.8 minutes on average after the hyperthermia started and the average number of replacements was 3.6. The highest outer shell temperature in patients with chest tumor and abdominal tumor averaged 38.5 and 39.1 ℃ at the first boot of the cooling system in the experimental group and 39.3 and 40.4 ℃ at the first replacement of the cooling water bag in the control group, respectively. The treatment with and without the intelligent temperature control system caused grade ≥Ⅱ empyrosis in 1 and 4 patients with chest tumor and in 0 and 3 patients with abdominal tumor, respectively. Conclusions In deep tumor hyperthermia, compared with the conventional cooling by replacement of water bags, the intelligent shell temperature control system can detect and cool the high-temperature zone in the outer shell at an earlier time, which effectively reduces the incidence of skin burn injury. Key words: Deep hyperthermia; Scalded skin; Temperature control

With the worsening of the global environment and the strengthening of people's awareness of environmental protection, the air pollution caused by the exhaust emissions of marine diesel engines has attracted extensive attention from the international community. Because the exhaust post-treatment technology does not need to be reformed for diesel engine, and the quality requirement of fuel is relatively low, domestic and foreign research and development institutions all attach great importance to the research of exhaust post-treatment technology. By analyzing the mechanism and main chemical reaction of SCR reaction, the overall design scheme of marine diesel engine exhaust intelligent emission reduction control system was completed in order to reduce the nitrogen oxides and solid particles in the exhaust of marine diesel engine. According to TierIII emission regulation and marine diesel engine exhaust, the hardware structure design and model selection of marine diesel engine exhaust intelligent emission control system are completed. In order to ensure that the emission of the control system can meet the requirements of nitrogen oxide conversion rate and ammonia gas escape quantity at the same time, the corresponding model prediction algorithm is designed in this paper. Through the analysis of experimental results, it is proved that the control system established in this paper can well meet the emission requirements of TierIII regulations. The research content of this paper can be applied in the field of shipping to meet the requirements of TierIII regulations and prepare for more stringent emission regulations.

Based on the requirements of the offshore wind farm construction, an intelligent remote control system has been proposed for jacking-up offshore platform. The system consists of a wireless LAN, a master control system, an intelligent node control system, and front sensors. The master control system is composed of a master control decision-making expert system, a malfunction diagnosis and disposal decision-making expert system, and database system, a virtual reality display system, and a wireless LAN system. The intelligent node control system consists of a control decision-making expert system, a jacking control system, a locking control system, a malfunction diagnosis system, executing controllers, status sensors, a database system, a pier-side control interface, and wireless LAN system. This remote control system enables a real-time analysis of the status of the platform, self adjusting of the platform, and memorizing previous decision for a better efficient control. This system supports independent execution with fault diagnosis & recovery ability. So it is recommended because it meets the requirements of offshore platform of wind farm construction.