DIGITAL CONTROL SYSTEM OF THE THYRISTOR REGULATOR IN THE NETWORK OF THE METALLURGICAL SHOP

The reasons for the deterioration of the electromagnetic environment in the workshop distribution network of a metallurgical enterprise with powerful valve regulators are considered. A local solution to the problem of improving electromagnetic compatibility is proposed by using a digital microcontroller control system for thyristor regulators of resistance mixers. The effect is achieved due to a more accurate fulfillment of the conditions for switching the gates of each phase at the moment of zero crossing. This allows not only to reduce the level of higher harmonics of the current in the distribution network and improve the symmetry of voltages, but also to increase the stability of the equipment.

Automated Microclimate Regulation in Agricultural Facilities Using the Air Curtain System

Creating and maintaining the microclimate in livestock buildings is associated with numerous engineering and technical challenges. Together with adequate feeding, the microclimate determines the health, reproductive ability, and production potential of the animals (obtaining a maximum amount of high-quality products). One of the deciding steps in improving the parameters of microclimate, i.e., temperature and humidity in agricultural facilities, particularly in livestock buildings, is to develop reliable and highly efficient air curtains in the vestibules. The objective of the manuscript is to investigate the parameters of the microclimate in livestock buildings using the air curtain, supported by automation and ICT technologies for rational operating modes. The presented theoretical and experimental studies on improving the microclimate parameters in livestock buildings were carried out using an innovative air curtain system. Its power is calculated based on the dimensions of the room, and the flow rate of warm air near the floor level is three times lower than at the installation site. The use of air curtains reduces consumption of thermal energy needed to maintain an optimal microclimate for livestock by 10–15%. Furthermore, the use of an automated digital control system maintains an optimal microclimate in the building. The developed energy-saving system for creating an optimal micro-climate in livestock buildings using air curtains was tested in a pigsty of the Research and Training Farm “Vorzel” of the National University of Life and Environmental Sciences of Ukraine, located in the Kiev region. The developed automated microclimate system using air curtains significantly improves the microclimate parameters and significantly reduces power consumption. The system can be further developed by adding remote control based on the Internet of Things (IoT) technology.

Design of a digital control system of disk gyroscope with orthogonal control circuit

This paper introduces a gyro control system with the quadrature control circuit. The control system realizes the automatic decoupling of driving mode and sensing mode. The quadrature control circuit eliminates the quadrature signal in the sensitive mode by applying a voltage to the quadrature control electrode. The time needed to adjust the voltage can be changed by adjusting the parameters of the controller. The control system is realized by a digital circuit. The feasibility of the design is verified by the test.

Deep Learning Control for Digital Feedback Systems: Improved Performance with Robustness against Parameter Change

Training data for a deep learning (DL) neural network (NN) controller are obtained from the input and output signals of a conventional digital controller that is designed to provide the suitable control signal to a specified plant within a feedback digital control system. It is found that if the DL controller is sufficiently deep (four hidden layers), it can outperform the conventional controller in terms of settling time of the system output transient response to a unit-step reference signal. That is, the DL controller introduces a damping effect. Moreover, it does not need to be retrained to operate with a reference signal of different magnitude, or under system parameter change. Such properties make the DL control more attractive for applications that may undergo parameter variation, such as sensor networks. The promising results of robustness against parameter changes are calling for future research in the direction of robust DL control.

Design of a digital control system of gyroscope

This paper introduces a digital control system of gyroscope. The control circuit includes amplitude control loop, phase control loop and detection circuit. The amplitude control loop realizes the stability of driving mode vibration signal amplitude. The phase control loop consists of coarse phase locking loop and precise phase locking loop. At the initial stage, coarse phase locking is used to realize the rapid start-up of the gyroscope. Then after resonance frequency settles into the lock-in range of PLL, precise phase locking is used to realize the precise phase locking. The detection circuit realizes the output of gyro angular velocity signal. The design is implemented on PCB. The test results show that the scheme can realize the stable operation of gyroscope.

Deep Learning Control for Digital Feedback Systems: Improved Performance with Robustness against Parameter Change

Training data for a deep learning (DL) neural network (NN) controller are obtained from the input and output signals of a conventional digital controller that is designed to provide the suitable control signal to a specified plant within a feedback digital control system. It is found that if the DL controller is sufficiently deep (four hidden layers), it can outperform the conventional controller in terms of settling time of the system output transient response to a unit-step reference signal. That is, the DL controller introduces a damping effect. Moreover, it does not need to be retrained to operate with a reference signal of different magnitude, or under system parameter change. Such properties make the DL control more attractive for applications that may undergo parameter variation, like sensor networks.