MICROCONTROLLER-BASED INTELLIGENT LIGHTING CONTROL SYSTEM WITH ADAPTATION TO ENVIRONMENTAL CONDITIONS

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.

A description of a new class of organizational and technical systems is given – intelligent road-building compaction control systems, the principles of operation of which provide for ensuring a given quality of compaction of asphalt mixtures in the process of road construction. The development of systems of that class is due, in the first place, to the transition to digital and intelligent control systems in construction. A scientific problem related to the relevance of creating methods for intelligent control of compaction of asphalt mixtures that affect the quality of road surfaces was formulated. To succeed, the usage of neural network structures was proposed. The usage will allow real-time monitoring of changes in the compaction quality index and efficient controlling of road machines using both the driver's manual means and the automatic compaction control system. The properties of the system under study – which determine the principles of its functioning: intelligence, informativity, speed, interconnectedness of subsystems, controllability and modularity – were presented. The above principles of the functioning of the proposed system, which are part of the methodology for managing the quality of asphalt compaction of pavement roads, were implemented in a set of methods and algorithms. Among them should be noted a new method of intelligent continuous control of compaction in the process of laying asphalt mixtures, an advanced method of intelligent prediction of compaction quality by vibrating rollers.

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 in commercial office environments is a major factor in workplace comfort, productivity, and stress. Modern work environments strive to improve these conditions by better selection of luminaires (fixtures), wall, floor, and furniture colour and texture, and intelligent lighting control that ensures that occupants each receive the proper amount of light needed at their workstations for the task at hand. Daylight infiltration is generally good for occupant comfort, and provides opportunities to harvest this daylight and save energy on electric lighting, provided that it is harnessed in a way that it does not over illuminate or cause glare. Building an intelligent lighting control system is challenging due to incompatible or sometimes conflicting lighting preferences from adjacent people or areas. Some office environments can be additionally challenging because of complex geometries, time-varying nondeterministic daylight contributions through windows, and glare. Here we address the challenges of meeting users' individual lighting preferences using a highly accurate illumination model to enable balancing the various lighting requirements among spatially grouped task areas, while minimizing the energy needed to do so (and in the future, minimizing the number of wireless sensors needed for this application). We propose an illumination model-based method and algorithm for intelligent open-loop lighting control, and present the results of a simulation study using a simplistic virtual room model to demonstrate the validity of our method. Daylight infiltration is to be addressed in future work.

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.

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

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.

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.

Learning from the behavior of the resident is essential in order to adapt the system and to provide intelligent control based on behavior patterns. Different homes have different conditions and habits which have to be taken into account for the intelligent system to be useful. However, even deeply ingrained habits are subject to change over time. Therefore, intelligent system has to respond to changing and diverse environment. In this paper the intelligent lighting control system based on resident’s behavioural patterns is presented that employs artificial neural networks for on-line learning and adaptation. In order to manage constantly growing data and dynamic environment problems, the latter algorithms have been improved with the proposed similarity threshold based data replacement algorithm which has been experimentally tested and compared with alternative algorithms.DOI: http://dx.doi.org/10.5755/j01.eee.21.2.8772

The intelligent lighting control system will unify the management of lighting equipment in outpatient buildings, inpatient buildings, and other buildings of the hospital, thereby improving the service quality of the hospital, providing a comfortable and relaxed working environment for medical staff, and providing a warm and comfortable treatment environment for patients. This project aims to develop a health rehabilitation environment lighting automation control system based on combining Zigbee Wide Ad Hoc Network and RFID (Radio Frequency Identification) technology. It can be customized according to the comfort needs of patients and can achieve lighting adjustments before the patient arrives. A PSO-based intelligent lighting control method has been proposed. To overcome the shortcomings of PSO such as being prone to local minima and premature convergence, a new PSO optimization method is proposed based on the inertia weight PSO and combined with genetic optimization theory. This method can not only learn experience from individuals in the group but also avoid the possibility of parent particles falling into local extremum. Compared with the original particle swarm optimization algorithm, the new particle swarm optimization algorithm can quickly find the optimal combination of lighting devices, improve computational efficiency by 6.208%, and also reduce the energy consumption of the calculated lighting devices, indicating the advantages of the new particle swarm optimization algorithm.

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

To intelligently control and adjust LED lighting network system, to make use of the sensor technology, wireless communication protocol, intelligent control technology, it overcomes the difference of the various technical standard, the lack of communication that is problem to impede the promotion of the intelligent lighting. Extending the conventional control method with intelligent technology, planning scheme according to the functions, the design carried out the three respectively subsystems, then the debugging and fusion of the software and hardware. By using the method of software, the high or low level of I/O output can simulate PWM control signal whose duty cycle of the PWM can be adjusted. The brightness data collected from the environment is changed into PWM control information. Using acoustic sensors and temperature sensors and voltage sensors to further adjust the distribution curves of the light and color, these collected data are turned into PWM fine tuning signal. The wireless intelligent lighting control system designed can well solve problems such as the large regional span, the high cost of the network transmission and the uncertain of the node number.