Algorithmic Support of Adaptive Automatic Control Systems with Data Compression

Introduction. The exponential growth of measurement information caused by ongoing complication of technical and production facilities necessitates the development of improved or brand new information and measurement systems, including those performing adaptive automatic control functions. Automatic criteria-based selection and reduction of measurement information continuously supplied by multi-parameter sources characterizing the objects under study require algorithms ensuring reconfiguration of automatic control systems during operation. In comparison with automatic control systems based on time-division channelling, the considered adaptive systems provide timely information on the pre-emergency and emergency operation of a facility.

Aim. To develop an algorithmic support for adaptive automatic control systems using asynchronous-cyclic and parallel-sequential operating algorithms, as well as to compare the proposed algorithms in terms of their, control reliability, compression ratio, operation speed and the error associated with multi-channelling.

Materials and methods. The algorithms proposed for supporting the operation of adaptive systems were developed on the basis of queuing theory and simulation modelling using the MatLab/Simulink programming languages, C++.

Results. The developed algorithmic support for automatic control systems based on asynchronous-cyclic analysis of deviations allows the amount of redundant information to be reduced by more than 4 times and the operation speed to be increased by 1.5 times. The developed algorithmic support for automatic control systems based on parallel-sequential analysis of deviations allows the error associated with multi-channelling to be reduced by 1.4 times, thereby bringing the control reliability of such systems closer to that of continuous-control systems. An analysis of the graphs of the error associated with multi-channelling showed that the automatic control systems based on parallel-sequential operational algorithms are invariant to the law of distribution of input quantities, compared to the systems based on asynchronous-cyclic operational algorithms.

Conclusions. The proposed algorithmic support can significantly decrease the redundancy of information and improve the metrological characteristics of automatic control systems. The use of the developed algorithms in automatic control systems based on time-division channelling render their control reliability comparable with that of continuous-control systems.

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