Digital Control System Research Articles

Review on FPGA Implementation of CORDIC Algorithm

The Coordinate Rotation Digital Computer (CORDIC) algorithm has emerged as a pivotal method for executing trigonometric and various mathematical operations within digital systems. Field-Programmable Gate Arrays (FPGAs) have witnessed a remarkable surge in adoption for implementing the CORDIC algorithm owing to their inherent flexibility and exceptional performance capabilities. This paper endeavours to provide a comprehensive overview of FPGA implementations of the CORDIC algorithm, elucidating both the advantages and challenges associated with this methodology. It thoroughly examines various FPGA architectures customized for CORDIC implementation, meticulously analyzing their respective trade-offs regarding resource utilization, performance metrics, and accuracy levels. Moreover, the paper explores numerous applications where the FPGA-based CORDIC algorithm shines, illustrating its adaptability across diverse domains like digital signal processing and control systems. These applications underscore the algorithm's efficacy in addressing real-world challenges and its potential to significantly augment system performance and efficiency.By furnishing profound insights into FPGA-based CORDIC implementations, this paper serves as an invaluable resource for engineers and researchers keen on harnessing the capabilities of FPGAs for high-performance mathematical computations in digital systems.

Modernization of digital food safety control.

Foodborne illness remains a pressing global issue due to the complexities of modern food supply chains and the vast array of potential contaminants that can arise at every stage of food processing from farm to fork. Traditional food safety control systems are increasingly challenged to identify these intricate hazards. The U.S. Food and Drug Administration's (FDA) New Era of Smarter Food Safety represents a revolutionary shift in food safety methodology by leveraging cutting-edge digital technologies. Digital food safety control systems employ modern solutions to monitor food quality by efficiently detecting in real time a wide range of contaminants across diverse food matrices within a short timeframe. These systems also utilize digital tools for data analysis, providing highly predictive assessments of food safety risks. In addition, digital food safety systems can deliver a secure and reliable food supply chain with comprehensive traceability, safeguarding public health through innovative technological approaches. By utilizing new digital food safety methods, food safety authorities and businesses can establish an efficient regulatory framework that genuinely ensures food safety. These cutting-edge approaches, when applied throughout the food chain, enable the delivery of safe, contaminant-free food products to consumers.

Temperature control of atomic gas chamber using a nonmagnetic heating chip fabricated on quartz substrate

Nonmagnetic electrical heating and temperature sensing chip fabricated on quartz substrate is developed, and a high-precision digital temperature control system is designed based on this chip. The heating resistance and temperature sensing resistance are prepared by depositing two layers of Ti/Pt alloy electrodes on quartz substrate through magnetic field cancellation design. The temperature coefficient of fabricated Ti/Pt temperature sensing resistance is +0.197%/℃. The simulation results show that the residual magnetic field generated by the heating current in the atomic gas chamber closely adjacent to the chip is less than 0.1 nT. Temperature control in the range of 100~150 ℃ is realized, and the temperature stability is about 0.02 ℃. Due to the high light transmittance of quartz glass, this heating chip has significant advantages for optical integration and miniaturization of atomic magnetometers.

Применение ультрафиолета для предпосевной обработкой семян

Modern methods of pre-sowing seed treatment disinfect seeds, increase yield and plant resistance to adverse environmental factors, and stimulate plant immunity. Among the methods of electromagnetic impact on bioobjects, irradiation of seeds with ultraviolet light is simple, energy-efficient, economically beneficial and environmentally safe. The research aimed to study the effect of UV irradiation for pre-sowing treatment of thuja seeds and empirically determine the effective dose of UV irradiation. To maintain the required UV irradiation dose, the authors developed a digital control system on ATMEGA128A microcontroller (ATMEL). The working area of a 12 × 12 UV matrix consisting of 200 UV LEDs was 144 cm2 . The distance from the UV LEDs to the irradiated seeds was about 2 cm. The UV dose of the matrix was controlled by monitoring the voltage drop on the NSL-19M51 photoresistors. The irradiance of the LEDs in the UV-A (UV-A) zone corresponded to 98%. In each series, 100 seeds of thuja occidentalis were irradiated; the experiments were repeated four times. The authors studied UV irradiation doses of 2 kJ/m2 , 3 kJ/m2 , and 4 kJ/m2 . Seeds of thuja occidentalis without UV irradiation treatment were used as a control. The effective dose of UV-irradiation of seeds was determined empirically. The determined UV irradiation dose of 2 kJ/m2 is able to increase seed germination energy by 12.8% as compared to the control. Statistical processing of empirical data showed satisfactory accuracy of the conducted experiments. The accuracy index of the experiment amounted to P=1.76%±0.65%, for the control (without UV irradiation) - P=1.33±0.47%.

Determining the stability region in the plane of parameters and quality indicators of linear discrete automatic control systems by D-partitioning method

The problem of constructing the boundary of the stability region (BSR) of linear discrete automatic control systems in the plane of the system parameters, which are linearly included in the coefficients of the characteristic equation, and quality indicators of the transient process (stability degree, fluctuation degree or attenuation factor) by the D-partition method is considered. The shifted and fictitious characteristic equations for BSR construction in the area of parameters and quality indicators are introduced. It is shown that the quality indicators are non-linearly included in the coefficients of the characteristic equation, therefore it is impossible to construct the BSR of discrete automatic control system using the classical D-partition method. Constructing of digital control system BSR of spaceship state using one coordinate in the plane of the system parameter- stability degree is considered. The BSR is obtained using the previously proposed by the authors method of constructing the region of stability in the plane of two parameters, one of which is nonlinearly included in the system equation. At the same time, the construction of the entire D-partition curve, special straight lines, and the use of Neimark hatching is excluded, and computer realization of the limit of stability region is ensured. The obtained BSR family in the plane of the parameter and at different values of another system parameter which is nonlinearly included in the coefficients of the shifted characteristic equation makes it possible to estimate, and for the parameter values on the boundary of the stability region of the BSR family, to determine the stability degree.

Трансформация оперативного управления эксплуатацией станков, станочных комплексов с помощью «Системы операционного менеджмента»

The article focuses on the potential integration of the SFM digital control system into production. To achieve a more accurate implementation of the dSFM system, the article identifies its strengths and weaknesses. It evaluates and outlines the factors contributing to the successful implementation of the dSFM system in production. The article also analyses the traditional Lean manufacturing system, the analogue SFM system and its digital version. The study scrutinised the manner in which workers interact with the «System of Operations Management» with the purpose of refining its assimilation into manufacturing processes and enhancing employee output.

METHOD OF DATA COLLACTION AND IT DISPLAYING IN A GRAPHICAL INTERFACE FROM AUTOMATIC CONTROL UNITS OF COMPLEX OBJECTS

Complex objects, characterized by intricate operations, interconnected components, and dynamic behaviors, pose unique challenges for digital control systems. This article highlights the importance of automated digital control systems in managing these complexities, emphasizing their crucial role in ensuring safety, reliability, and efficiency. Addressing these challenges involves dealing with system complexity, non-linear dynamics, uncertainties, real-time requirements, data quality, and the need for optimization. Furthermore, ensuring regulatory compliance, safety, scalability, energy efficiency, and cybersecurity adds additional layers of complexity. This article explores the challenges faced by digital control systems when dealing with complex objects-systems with intricate operations and interconnected components. It emphasizes the vital role of automated digital control in ensuring safety, reliability, and efficiency in such scenarios.

Theoretical substantiation of the requirements for an intelligent video monitoring system for analyzing the physiological state of cows and predicting its changes

At the present stage of development of dairy farming, the main task facing the industry is the effective management of all processes that ensure the operation of a farm with a large livestock. This task will not be achievable without the use of digital intelligent production control and management systems, tracking the health of animals and their productivity. There are many systems that integrate into production and allow you to monitor the health of cows on a dairy farm. These systems are based on the identification, tracking and collection of information about the physiological state of animals through various sensors. However, all these systems are expensive, demanding to maintain, often fail due to aggressive operating conditions. The article considers the possibility of using an intelligent video monitoring system to analyze the physiological state of cows and predict its changes. To substantiate the requirements for an intelligent video monitoring system of the physiological state of cows, a mathematical model of the life of productive cows in the form of a graph of states is proposed. This method graphically displays the possible states of the system and their possible transitions from state to state. Having constructed a graph of states, relying on the central probability theorem for event flows, it is possible to determine the probability and intensity of state transitions using differential equations. For the functioning of the video monitoring system for analyzing the physiological state of cows and predicting its changes, the proposed mathematical model can be the basis of the system and be based on the collection and analysis of video information about animal behavior. When covering the entire territory of the animal's living space with video cameras, the intelligent video monitoring system will be able to provide early diagnosis of changes in the physiological state of the observed animals and issue a warning, which will allow for timely therapeutic and preventive measures.

Design of Digital Control System for Line Following Robot

Design of mobile robots has become an increasingly growing trend in the technology of modern times. They are very attractive engineering systems, not only because of many interesting theoretical aspects concerning kinematics, intelligent behavior and autonomy, but also because of applicability in many human activities. A typical example is the line following robot (LFR). In order for a LFR to function effectively, it must demonstrate excellent line tracking control. This is achieved by having accurate and responsive control algorithms as well as high precision color sensor systems. This paper proposes a system to show that good line tracking performance can be achieved with moderately simple digital control algorithms. The platform used is a differentially driven wheeled robot constructed using the Lego Mindstorms components. The simulation models are presented and analyzed using MATLAB Simulink . The main programming environment is the EV3 Software.

Real-Time Plasma Magnetic Control System with Equilibrium Reconstruction Algorithm in the Feedback for the Globus-M2 Tokamak

To control the plasma shape during a tokamak discharge, it is necessary to calculate the plasmashape in real-time. The rate requirements for the shape calculations are especially high for tokamaks with asmall radius, such as Globus-M2 (St. Petersburg, Russia). A real-time magnetic plasma control system forthe Globus-M2 tokamak with flux and current distribution identification (FCDI) algorithm for the plasmaequilibrium reconstruction in feedback is presented. The control system contains discrete one-dimensionaland matrix proportional-integral-derivative controllers synthesized by the matrix inequality method usingthe plasma LPV model calculated on experimental data, and carries out the coordinated control of the plasmaposition and shape as well as the compensation for the scattered field of the central solenoid. The FCDI algorithmis improved for the operation in the real-time mode, and makes it possible to reconstruct the plasmashape in 20 μs. The digital control system with a feedback algorithm was simulated on a real-time test bench,consisting of two Speedgoat Performance Real-Time Target Machines (RTTM), and demonstrated the averageTask Execution Time (TET) value in 67 μs.

Experimental study of automated soil density control system of garlic planting machine

An automated system for adaptive regulation of soil density has been developed, which makes it possible to improve the quality of garlic incorporation when planting within the range of soil density regulation in the range of 1.2 -1.4 g/cm?. A methodology has been developed for conducting experimental studies of a machine for planting garlic with an installed automatic monitoring and control system for regulating soil density during planting. The results of experimental studies of the uniformity of soil compaction using a compaction roller with an automatic density control system and a closing device represented by a skid-type harrow indicate that after passing through a skid-type harrow, the value of the studied parameter increased by 18% relative to the initial state of the soil. The results of experimental studies of the quality indicators of the planting machine without an automatic monitoring and control system indicate a deterioration in the quality of the process of planting garlic bulbs with increasing forward speed in the range from 0.8 to 1.2 m/s at values of the coefficients of variation of the depth of planting of garlic bulbs ?_Hl from 32% to 42%. The results of experimental studies of the influence of a digital system for automatic control and management of garlic planting indicate the prospects of conducting research in this direction, which is confirmed by an increase in the quality indicators of the planting machine by 15% in comparison with the closing organ in the form of a skid-shaped harrow.

Intelligent diagnosis and prediction of turbine digital electro-hydraulic control system faults: Design and experimentation.

A physical modeling approach was adopted to build a Digital Electro-Hydraulic Control (DEH) system simulation model and the fault models using the SIMULINK tool. This research combined the advantages of the gray system and neural network to build a multi-parameter gray error neural network fault prediction model for the first time. Furthermore, an embedded platform for intelligent fault diagnosis and prediction was developed using an Application Specific Integrated Circuit chip. The results show that the simulation model of the DEH system has good performance. A jam fault, internal leakage, and a device fault could be accurately identified through the fault diagnosis model. The multi-parameter gray error neural network prediction model improves the accuracy of fault prediction. The embedded platform developed by the Application Specific Integrated Circuit chip solves the problem of transmission limitation and insufficient computing power. It realizes the intelligent diagnosis and prediction of DEH system faults and guarantees the regular operation of the DEH system.

Research on an Active Hydrogen Maser Digital Circuit Control System Based on FPGA.

A hydrogen maser is a high-precision time measurement instrument with high frequency stability and low frequency drift, which is widely used in satellite navigation, ground time keeping, frequency measurement, and other fields. An active hydrogen maser (AHM) is better than the current space passive hydrogen maser (PHM) in orbit in terms of its frequency stability and drift rate, but it has the disadvantages of large volume and weight. To further reduce the volume and weight of the circuit, this paper demonstrates a digital circuit control system based on a field-programmable gate array (FPGA). It uses digital temperature control, digital detectors, digital down-conversion, digital phase-locked loops, and other digital methods for temperature control, cavity auto-tuning, and crystal phase locking, which improve the integration and flexibility of the circuit system. Meanwhile, a tuning method based on hydrogen flow is proposed, which effectively solves the problem of fluctuations in hydrogen maser resonance frequency with changes in the external environment. Our experimental results show that the designed digital circuit control system meets the requirements of an oven-controlled crystal oscillator (OCXO) loop and a cavity loop. Its frequency stability can reach 2.6×10-13/1 s and 1.4×10-15/10,000 s, which is close to the stability index of ground active hydrogen maser. This scheme has certain practical engineering value, and can be used in the design of hydrogen masers for next-generation space navigation satellites, deep space exploration, and space stations.

Stages and main tasks of the century-long control theory and system identification development

The article provides a review of the mathematical description of the dynamics of continuous and discrete linear stationary systems and objects, used at the development stage of the classical theory of automatic control in the form of mathematical models of the «input-output» type. The time and frequency characteristics of continuous and discrete control systems are described, typical links of stationary systems are considered, parametric discrete models of objects as part of typical digital control loops are presented. Stochastic discrete autoregressive models of stationary time series used to describe the dynamic objects in the synthesis of digital control systems are considered. A review of standard control laws for the implementation of continuous and discrete controllers has been completed. A method for synthesizing discrete controllers for multidimensional controlled objects with different, unknown and changing delays is considered, through which variable delays are compensated in the characteristic equation of a closed-loop control system. A common technique for synthesizing one-dimensional and multidimensional controllers for stochastic objects with delays based on ARMAX models is considered. An analysis of approaches to identifying delays in controlled objects is carried out and a method for identifying delays when using input-output models is considered, based on the calculation and comparison of impulse responses for extended and non-extended models of the controlled object. An analysis of the advantages and disadvantages of «input-output» type models is given, as well as the possibilities of their application for solving various classes of control theory problems.

Эффект синергизма для управления посевными качествами семян люцерны изменчивой с элементами нейросети для контроля дозы УФО

The article presents studies to identify the greatest synergy effect for managing the sowing qualities of alfalfa seeds of variable Victoria with the use of neural network elements to control the dose of ultraviolet irradiation. The synergistic effect occurs when the seeds are simultaneously exposed first to ultraviolet radiation and then to a silicon-containing preparation of nanosilicon, or first to treatment with a preparation of NanoSilicon, and then to ultraviolet radiation. In both cases, changes in the sowing qualities of seeds were observed. The seeds were irradiated on a mobile LED UV irradiation unit using end-to-end digital energy-saving technologies with neural network elements to control the dose of UFOs with a VEML6070 digital sensor from the manufacturer Vishay Semiconductors. The TKS– ABC device measured the energy illumination of UV LEDs at a height of 70 mm, which showed that UV-A radiation is 95.67% at an average energy illumination of 3.137 W/m2, UV-B radiation is 3.41% at 0.112 W/m2 and UV-C radiation is 0.91% at 0.030 W/m2. The conducted studies have revealed that the greatest synergistic effect for managing the sowing qualities of alfalfa seeds occurs when alfalfa seeds are treated first with a nanosilicon preparation, and then with UFOs. As a result of the management of the sowing qualities of alfalfa seeds, which is involved in the implementation of the proposed sequence of pre-sowing seed treatment, an increase in laboratory germination was obtained by 6% at HCR05 – 4%; the length of the sprout up to 2.4 cm and the root up to 1.5 cm; the degree of development of seedlings up to 3.0 points and growth strength up to 29.8%. Keywords: ALFALFA VARIABLE, LABORATORY GERMINATION, DEGREE OF SEEDLING DEVELOPMENT, GROWTH VIGOR, SYNERGISM, ULTRAVIOLET IRRADIATION DOSE, DIGITAL CONTROL SYSTEMS

Structural and Parametric Synthesis of Neural Network Controllers for Control Objects with Limiters

The article presents a methodology for the synthesis of digital control systems for nonlinear objects with limiters under conditions of incomplete information. Closed-loop tracking systems with negative feedback are considered. Artificial neural networks are proposed to build a controller, which is included in series with the control object. This approach is effective when known classical methods do not allow to synthesize control. This is the case, for example, if the mathematical model is essentially nonlinear and is not fully defined. The developed methods allow us to expand the class of technical systems, for which the direct (without using various kinds of simplifications) synthesis of control laws that are close to optimal is possible. In addition, neural network controllers possess the properties of robustness, adaptivity, and are initially digital, i.e. those qualities, which are very much in demand in practice. In article main attention is given to such problems, as a choice of neural network structure for neural simulator and neural controller, construction of training sample, ensuring convergence of the process of weights correction. For training neural networks the method of back propagation of error is used as a basic one. The effectiveness of the proposed technique is demonstrated by the example of the synthesis of a neuroregulator for a specific technical object and its comparison with classical control systems. It should be noted that today neural network technologies are widespread enough in various spheres of activity. The successes demonstrated in sound processing, image processing, automatic translation, in navigation systems, in big data processing are impressive. However, their application in automatic control systems is not so widespread. The authors of this article believe that the potential of artificial neural networks can be used in this direction. It should be understood that the use of neural networks is effective only under certain conditions and properties of the control object.

Design of Discrete and Hybrid Nonlinear Control Systems

In this article the new method of discrete control systems design for nonlinear plants with differentiable nonlinearities is suggested. The increasing demands on the quality of control processes and the widespread use of computer technology provide ample opportunities for the design and implementation of digital control systems. However, discrete models of control plants are needed to solve this problem. In the case of linear plants, such models are created on the basis of z-transformation, Euler or Tustin formulas. In the case of nonlinear plants, these transformations are not applicable, so a large number of approximate discretization methods have been developed to date. Euler and Runge-Kutt transformations are used for these purposes most often, but they lead to satisfactory results only with very small period of discretization. In the case of automatic control systems, this requires the use of digital automation tools with very high speed, which is often economically impractical. Methods of discretization with a long period were most often developed on the basis of decomposition into series of the right-hand sides of the differential equations, transformed on Euler. Here, firstly, the problem of selecting the number of the series members, which to be retained arises, and secondly, already in the third or fourth order of the plant, the calculating ratios turn out to be extremely complex. The discretization method suggested below differs in that it is not the equations of nonlinear plants in the Cauchy form that are discretized, but the corresponding quasilinear model. In this case, a modified trapezoid method is used, and the discretization purpose is not the most accurate approximation of the original equations of the plant, but the stability of a closed nonlinear control system with rather big period. This system is designed using the algebraic polynomial-matrix method for designing of the nonlinear control systems. As a result, a hybrid nonlinear system with fairly simple algebraic calculation expressions is formed. The suggested approach makes it possible to create the control systems for nonlinear controlled plants using conventional computational automation tools.

Performance analysis of digitally controlled nonlinear systems considering time delay issues

In this paper, a comprehensive investigation into discretization, effective sample time selection considering delays in the system, and time and frequency domain analysis of a DC-DC buck converter, which plays a vital role in photovoltaic (PV) systems, is conducted to enhance the understanding of their dynamic behavior, optimize control algorithms, improve system efficiency, and ensure reliable power conversion in photovoltaic applications. To effectively address the non-linear behavior and enhance digital control of a buck converter by selecting the best sample time, several approaches can be employed. These include accurate modeling and identification of non-linear elements, development of advanced control algorithms that account for non-linearities, implementation of adaptive control techniques, and utilization of feedback mechanisms to compensate for deviations from linearity. By considering and mitigating the non-linear behavior, digital control systems can achieve improved accuracy, stability, and transient behavior in regulating the buck converter's output waveforms (voltage or current). The results of the study demonstrated that the trapezoidal integration method which is also known as bilinear approximation, or Tustin's approach outperformed other commonly used discretization methods, such as first-order hold (FOH), zero-order hold (ZOH), impulse response matching (impulse invariant), and matched pole-zero (MPZ) technique, in dual-domain (both time and frequency) analysis. The key finding highlighting the superiority of the bilinear approximation was its ability to achieve the closest match in the frequency domain bridging the continuous-time and discrete systems. This finding emphasizes the significance of the bilinear approach in preserving the frequency characteristics of the original continuous-time system during discretization. By employing this method, the discrete system closely approximated the behavior of its continuous-time counterpart, ensuring accurate frequency-domain representation.

Optimized Discrete-Time Current Control for IPMSM Drives

Designing the current controller directly in the discrete-time domain is essential to high-speed applications, mainly due to the delay inherent to the digital control system. Active-damping (AD) is usually included to improve the disturbance rejection. However, the continuous-time form of the AD element is normally followed simply in the discrete-time domain design, which causes the dynamic performance and the anti-disturbance performance cannot be taken into account well. To easy the confliction, a novel AD loop, dedicated to the discrete-time plant, is proposed. In this design, the AD element is no longer limited to be a single real gain, as commonly seen in the continuous-time domain representing the active resistance. Alternatively, it is designed with the feedback control theory, allowing both the tracking response and disturbance response to be designed as required respectively. As a result, the dynamic response and disturbance rejection can be determined independently, and the parameter robustness can also be designed intentionally to a great extent. Besides, to reduce computation load in practice, a discrete-time IPMSM’s model with low computation intensity and high accuracy is presented in this paper. Some experimental results are reported to demonstrate the performance of the discrete-time control designed in this paper.

Design of a Three-Port Integrated Topology to interface electric vehicles and renewable energy sources

This work proposes the design and analysis of an off-board Three-Port Integrated Topology (TPIT). TPIT is used to interface Electrical Vehicles (EVs) and Renewable Energy Sources (RES) from solar electrical phenomenon (PV) panels with the power grid. The TPIT consists of three power converters sharing one common DC link. It can be operated in four completely different modes towards the long run sensible grids. The EV battery area unit is charged with energy from the power grid through the Grid-to-Vehicle (G2V) operation mode. The EV batteries deliver a part of the stored energy back to the power grid through the Vehicle-to-Grid (V2G) operation mode. The energy created by the PV panels is delivered to the electrical grid through the Renewable-to-Grid (R2G) operation mode and the energy created by the PV panels is employed to charge the EV batteries through the Renewable-to-Vehicle (R2V) operation mode. In addition to individual action, the reorganization of those modes leads to hybrid operational modes. This work plan is to propose a power theory to regulate the TPIT and this current control strategy controls the current in AC and DC sides of the TPIT respectively. Also, the features of the developed TPIT prototype, including the hardware and the digital control system are designed. The result portrays the analysis of TPIT operation modes are presented.