Проектирование архитектуры информационной системы управления энергоресурсами
Cyber-physical systems (CPS) are widely used due to the “Industry 4.0” concept development within which digital enterprise transformation and the use of new management techniques based on the Internet of Things (IoT) and Big Data analytics assume primary importance. In general, CPS is a class of information systems whose computational elements are integrated into physical processes and objects; such systems can interact with each other using Internet protocols. The growing number of situations requiring CPS implementation determines the necessity of CPS design that takes into account the specific factors of a subject area. The CPS structure includes hardware and software which in many ways affect the security and cost of a technical solution, the convenience of user interaction with the system. A significant CPS programs feature is ensuring long-term performance and high sustainability which is largely complicated by the lack of unified solutions (templates) for CPS software design. This obstacle affects the realization of other software requirements as well. The purpose of the study is to identify ways to optimize the cost/quality ratio of the CPS software being designed that uses the technologies of the Internet of Things and present findings in the form of recommendations suitable for further use. One of the methods that realize complex organizational and technical solutions evaluation is Value Engineering (VE). CPS software functions have been identified and the anticipated system software structure has been determined. The results of applying the VE method to CPS software have been reflected and the conclusions considering the practical significance of the study have been drawn. The analysis has been carried out within the priority area of scientific development established in the National research university Higher school of economics (Perm) – “Research on control methods in cyber-physical systems”.
Architecture of the compressor equipment cyber-physical system (CPS) based on the InfluxData IoT platform is proposed. CPS consists of three subsystems: a subsystem of a physical object,
a digital twin and an interface. As a technical implementation of the IoT controller, a measuring and control module based on a data acquisition, data transfer and control device — VIDA350. The basic methods of processing raw data from energy meters and sensors of technological parameters, implemented in blocks of on-line and offline calculations are given. The organization of the digital twin of the compressor using the database of time series InfluxDB and the relational database PostgreSQL. Grafana system and FreeCAD is used for visualization of equipment in 3D.
Introduction. The gained experience in the field of building automation and IoT technologies yields a new approach to the management of engineering subsystems that provides stated parameters of operation quality throughout the entire building lifecycle. This paper explores compensatory and predictive algorithms in the scope of the aforementioned approach to manifest control over building climate parameters utilizing IoT controllers. This research aims to improve the management efficiency of smart house engineering subsystems through the implementation of a control system (CS) capable to compensate disturbances and predict their variations using an IoT controller and an analytical server.
Materials and methods. In order to improve the quality of control, various algorithms based on analysis of data collected from controllers can be employed. The collected data about the object accumulated over the entire period of operation can be used to build a model for the purposes of predictive control. The predictive control allows forecasting the parameters having an effect on the object and compensating it beforehand under the inertia conditions. The continuous adaptation and adjustment of the CS model to operating conditions allows permanent optimizing the settings of the control algorithm ensuring the efficient operation of local control loops.
Results. The CS is based on an IoT controller and able to predict and compensate potential disturbances. The compensation algorithm is updated depending on the behavior of the object properties, quality of control and availability of data most suitable for identification.
Conclusions. The capabilities of the control system based on the IoT controller and generation of a compensatory and predictive control signal with the algorithm hosted at a cloud server are demonstrated on the indoor temperature control model. The following simulation models of the indoor temperature variation process are considered: model without CS, model with proportional plus integral controller with disturbance compensation and model with IoT controller-based CS with disturbance compensation. Structural and parametric identification of the models are accomplished by means of active experiment.