High-speed Processing Research Articles

Non-Destructive Measurement of Quality Parameters of Apple Fruit by Using Visible/Near-Infrared Spectroscopy and Multivariate Regression Analysis

The quality assessment and grading of agricultural products is one of the post-harvest activities that has received considerable attention due to the growing demand for healthy and better-quality products. Recently, various non-destructive methods have been used to evaluate the quality of agricultural products, which are very desirable and faster and more economical than destructive methods. Optical methods are one of the most important non-destructive methods that use the high speed of light detection and computer data processing and are able to evaluate the quality and classification of products with high accuracy. Among the optical methods, visible–near-infrared (Vis/NIR) spectroscopy is considered one of the most accurate methods. In this research, Vis/NIR spectroscopy technology was used in the spectral range of 350–1150 nm for non-destructive detection of some quality parameters including pH, TA, SSC, and TP of two varieties of Red Delicious and Golden Delicious apples. Various pre-processing models were developed to predict the parameters, which brought the desired results with high accuracy so that pH prediction results were for yellow apples (RMSEC = 0.009, rc = 0.991, SDR = 2.51) and for red apples (RMSEC = 0.005, rc = 0.998, SDR = 2.56). The results for TA were also (RMSEC = 0.003, rc = 0.996, SDR = 2.51) for red apples and (RMSEC = 0.001, rc = 0.998, SDR = 2.81) for yellow apples. The results regarding SSC were for red apples (RMSEC = 0.209, rc = 0.990 and SDR = 2.82) and for yellow apples (RMSEC = 0.054, SDR = 2.67 and rc = 0.999). In addition, regarding TP, the results were for red apples (RMSEC = 0.2, rc = 0.989, SDR = 2.05) and for yellow apples (RMSEC = 1.457, rc = 0.998, SDR = 1.61). The obtained results indicate the detection of the mentioned parameters with high accuracy by visible/infrared spectroscopic technology.

An efficient low power method for FinFET domino OR logic circuit

Advancement in the metal oxide semiconductor field effect transistor (MOSFET) technology leads to large power dissipation, and propagation delay due to extreme scaling of the transistor. So, very large-scale integration (VLSI) industry requires alternative options to meet the demands of the customers. Fin-shaped field effect transistor (FinFET) is new innovative device to replace the MOSFET technology in ultra-deep submicron (ultra-DSM) regime. FinFET mitigates power dissipation to the large extent as compared to the MOSFET, but still the impact of power dissipation degrades the circuit performance. Leakage reduction techniques are further needed in ultra-DSM regime to reduce the power dissipation. Domino logic is commonly used in large memories, and high-speed processors. In this article, a low power domino logic is proposed using FinFET devices. The proposed method is compared to the existing similar domino logic approaches for the different performance metrics at 7 nm technology node using Cadence's tools. The proposed method effectively reduces the leakage power dissipation, and delay penalty for the different logic circuits. The reliability of the domino OR logic is checked by estimating the temperature, and multiple parallel fins variations. The proposed method has a high noise tolerance capacity in term of unity noise gain (UNG) for the domino OR logic as compared to the existing approaches.

Scalable Networks of Neuromorphic Photonic Integrated Circuits

Neuromorphic photonic integrated circuits over silicon photonic platform have recently made significant progress. Photonic neural networks with a small number of neurons have demonstrated important applications in high-bandwidth, low latency machine learning (ML) type signal processing applications. Naturally an important topic is to investigate building a large scale photonic neural networks with high flexibility and scalability to potentially support ML type applications involving high-speed processing of a high volume of data. In this paper we revisited the architecture of microring resonator (MRR) -based non-spiking and spiking photonic neurons, and photonic neural networks using broadcast-and-weight scheme. We illustrate expanded neural network topologies by cascading photonic broadcast loops, to achieve scalable neural network scalability with a fixed number of wavelengths. Furthermore, we propose the adoption of wavelength selective switch (WSS) inside the broadcasting loop for wavelength-switched photonic neural network (WS-PNN). The WS-PNN architecture will find new applications of using off-chip WSS switches to interconnect groups of photonic neurons. The interconnection of WS-PNN can achieve unprecedented scalability of photonic neural networks while supporting a versatile selection of mixture of feedforward and recurrent neural network topologies.

Deposition strategies for generating cuboid volumes using extreme high-speed directed energy deposition

Extreme high-speed directed energy deposition (EHLA) is a variant of directed energy deposition (DED-LB) developed at Fraunhofer ILT in cooperation with RWTH Aachen University. Because of a powder gas jet setup that is aimed at melting particles in the laser beam before they enter the melting pool, high process speeds of up to several hundred meters per minute and a layer thickness as thin as 25 μm can be achieved. EHLA is generally applied for rotationally symmetric coating applications. In previous experiments on a prototype machine of ponticon GmbH, EHLA was used for building up dense volumes, thus qualifying its use for additive manufacturing, now termed EHLA 3D. In this work, using iron-base alloy 1.4404 and a process speed of 40 m/min, cubic volumes are produced with EHLA 3D. Different deposition strategies commonly used in DED-LB are tested for their transferability to EHLA 3D. The results of different deposition strategies achieving the best near net shape geometry are shown in comparison to DED-LB. Furthermore, the influence of the deposition strategy and used technology on thermal management and microstructure are investigated. The best near net shape is achieved in this comparison using a contour-hatch strategy with 1.5 contours per layer and a 90° rotation of the hatch, both for EHLA and DED-LB. The microstructure of EHLA 3D built cubes is more similar to a typical laser powder bed fusion microstructure than to a typical DED-LB microstructure with respect to grain size and structure.

A High-Performance and Flexible Architecture for Accelerating SDN on the MPSoC Platform

Software-defined networking has been developing in recent years and the separation of the control plane and the data plane has made networks more flexible. Due to its flexibility, the software method is used to implement the data plane. However, with increasing network speed, the CPU is becoming unable to meet the requirements of high-speed packet processing. FPGAs are usually used as dumb switches to accelerate the data plane, with all intelligence centralized in the remote controller. However, the cost of taking the intelligence out of the switch is the increased latency between the controller and the switch. Therefore, we argue that the control decisions should be made as locally as possible. In this paper, we propose a novel architecture with high performance and flexibility for accelerating SDN based on the MPSoC platform. The control plane is implemented in the on-chip CPU and the data plane is implemented in the FPGA logic. The communication between the two components is performed using Ethernet communication. We design a high-performance TCAM based on distributed RAM. The architecture employs a pipeline design with modules connected via the AXI Stream interface. The designed architecture is flexible enough to support multiple network functions while achieving high performance at 100 Gbps. As far as we know, the architecture is the first proposed in the design of a 100 Gbps system.

Numerical investigation of heat transfer enhancement in microchannel heat sink with fan cavities using secondary channels and ribs

A computational three-dimensional modeling of microchannel heat sink (MCHS) with fan cavity and four different rib configurations along with secondary channels (SCs) has been performed in detail to identify the influence of geometrical parameters on characteristics of heat transfer and provide insight into optimum configuration. The adverse effect of high processing speed and heat flux demands lower operational temperature at the expense of high pumping power in order to increase the lifespan of electronic equipment. Single phase, laminar flow of fluid is considered in the Reynolds number range from 136 to 588. The novel design of the SC benefits heat transfer enhancement by the increase in flow area, originates secondary flows subsequently transforms into symmetric counter-rotating vortices on the basis of rib, however, the influence of the rib blocking effect also depletes, resulting in minimal pressure drop. The comparison between various rib structures confirms that the FC-FTR-SC configuration acquired superior heat transfer performance with a TP of 2.07, at Re = 261. The FC-FTR-SC configuration has a great deal of evidence that pumping power decreases by 10.1% and TP increases by 11.7% as β increases from 0.5 to 1.25. The influence of four geometric parameters: relative width of rib ( α), relative width of the SC ( β), relative length of cavity ( γ), and relative angle of the SC ( ϕ) on heat transfer enhancement and pressure drop have been performed using parametric optimization, response surface methodology.

In-Depth Characterization of Laser-Welded Aluminum-and-Copper Dissimilar Joint for Electric Vehicle Battery Connections.

With advancements in the automotive industry, the demand for electric vehicles (EVs) has remarkably increased in recent years. However, the EV battery, which is a vital part of the EV, poses certain challenges that limit the performance of the EVs. The joining of dissimilar materials for different components affects the electrical and mechanical performances of EV batteries. Laser beam welding is a promising technique for joining Al and Cu for application in secondary battery fabrication because of the precise control over heat input and high process speed. However, the production of Al-Cu joints remains challenging because of the differences between their thermal and metallurgical properties and the resulting formation of brittle and hard intermetallic compounds, which reduce mechanical and electric properties. Thus, it is vital to characterize the weld to improve joint performance and enhance the laser welding process. This study investigates the joining of an Al alloy (AA1050) with Ni-coated Cu using a continuous-wave Yb fiber laser. The evaluation of the weld morphology showed a correlation between the weld characteristics and process parameters (laser power and welding speed). The weld interface width and penetration depth into the lower sheet (Cu) both increased with increasing heat input. Optical microscopy of the weld cross-section revealed many defects, such as voids and cracks. Scanning electron microscopy (SEM) with energy-dispersive X-ray spectroscopy (EDS) was employed to examine the weld microstructure. The composition analysis revealed the presence of mixed morphology of Al-Cu eutectic alloy (α-Al+Θ-Al2Cu) phase in the form of dendrites in the weld fusion zone with traces of the highly brittle Al4Cu9 phase at a high heat input condition. Furthermore, the electrical contact resistance of the weld seam was measured to determine the correlation between heat input and resistance. In addition, Vickers microhardness measurements were performed on the weld cross-section to validate the SEM/EDS results.

Influence of Heat Accumulation on Morphology Debris Deposition and Wetting of LIPSS on Steel upon High Repetition Rate Femtosecond Pulses Irradiation

The fabrication of laser-induced periodic surface structures (LIPSS) over extended areas at high processing speeds requires the use of high repetition rate femtosecond lasers. It is known that industrially relevant materials such as steel experience heat accumulation when irradiated at repetition rates above some hundreds of kHz, and significant debris redeposition can take place. However, there are few studies on how the laser repetition rate influences both the debris deposition and the final LIPSS morphology. In this work, we present a study of fs laser-induced fabrication of low spatial frequency LIPSS (LSFL), with pulse repetition rates ranging from 10 kHz to 2 MHz on commercially available steel. The morphology of the laser-structured areas as well as the redeposited debris was characterized by scanning electron microscopy (SEM) and µ-Raman spectroscopy. To identify repetition rate ranges where heat accumulation is present during the irradiations, we developed a simple heat accumulation model that solves the heat equation in 1 dimension implementing a Forward differencing in Time and Central differencing in Space (FTCS) scheme. Contact angle measurements with water demonstrated the influence of heat accumulation and debris on the functional wetting behavior. The findings are directly relevant for the processing of metals using high repetition rate femtosecond lasers, enabling the identification of optimum conditions in terms of desired morphology, functionality, and throughput.

On-chip ultra-compact nonvolatile photonic synapse

The important research content of modern communication systems is to realize high-speed, stable, and intelligent information transmission and processing. All-optical neural networks based on the silicon integrated technology and phase change materials (PCMs) can realize picosecond-level modulation speed, faster processing speed, and lower energy consumption compared with the traditional electrical communication system. The photonic synapse is the core component of the all-optical neural network module, but the existing photonic synapses based on PCMs require a modulation distance (MD) of several micrometers or even ten micrometers to achieve a large output intensity range. In this paper, we propose an ultra-compact nonvolatile photonic synapse, in which MD can be shortened to 1 μm, breaking the record of the minimum signal MD of the silicon photonic synapse using the PCMs. At the same time, the output intensity range of our synapse is almost twice that of the existing research. Based on this photonic synapse, we analyze the relationship between the output response and incident wavelength, which can help to design an ultra-compact photonic convolutional neural network. This work has great potential in future photonic computing and photonic communication technologies.

Lightweight and highly robust memristor-based hybrid neural networks for electroencephalogram signal processing

Memristor-based neuromorphic computing shows great potential for high-speed and high-throughput signal processing applications, such as electroencephalogram (EEG) signal processing. Nonetheless, the size of one-transistor one-resistor (1T1R) memristor arrays is limited by the non-ideality of the devices, which prevents the hardware implementation of large and complex networks. In this work, we propose the depthwise separable convolution and bidirectional gate recurrent unit (DSC-BiGRU) network, a lightweight and highly robust hybrid neural network based on 1T1R arrays that enables efficient processing of EEG signals in the temporal, frequency and spatial domains by hybridizing DSC and BiGRU blocks. The network size is reduced and the network robustness is improved while ensuring the network classification accuracy. In the simulation, the measured non-idealities of the 1T1R array are brought into the network through statistical analysis. Compared with traditional convolutional networks, the network parameters are reduced by 95% and the network classification accuracy is improved by 21% at a 95% array yield rate and 5% tolerable error. This work demonstrates that lightweight and highly robust networks based on memristor arrays hold great promise for applications that rely on low consumption and high efficiency.

An FPGA-Based Design of a Fault-Tolerant Shared Memory Structure

In this current era of smart computation, faster processing speed is needed. Execution of a process in a parallel manner can achieve higher throughput. For avoiding the Von-Neumann bottle-neck phenomena, the speed of the memories should be high. A high-speed memory can provide contiguous data to a high-speed processor that retains the high performance of that processor. Various high-speed memory technologies are existing in the market such as interleaved memory, cache memory, etc. Multiprocessing technology is also used to achieve high-performance computation. It is still challenging to make a high-speed memory device that can provide data to a multiprocessing system in a contiguous way. Shared memory can fulfill all of the requirements of a multiprocessing system. The efficiency of shared memory can be enhanced by introducing the fault-tolerant mechanism in it without affecting the inter-process communication, which will be discussed in this paper.

Special Issue on High-Speed Vision and its Applications

In recent years, advances in CMOS imagers and AI have rapidly expanded the application fields of image processing. Spatial resolution, sensitivity, dynamic range, etc. for devices have dramatically improved, while various recognition functions have been implemented with the introduction of learning-based information processing, making progress day by day. However, the temporal resolution or temporal dynamics of an image has been limited to the video rate level of processing, because image processing has been required to realize the functions of the human eye. In the case of processing for high-speed moving objects or controlling machine dynamics as machine eyes, rather than processing in the range visible to the human eye, high-speed vision, i.e., high-speed image processing in a bandwidth that covers the dynamics of the object, and a system that utilizes such processing, are required. This special issue summarizes such advanced research on high-speed vision, highlighting its current status and future development in the areas of devices, systems, and application developments. High-speed vision has entered a new era, as the basic technology and various applications have been developed and new functions are being added one after another. We hope that this timely special issue will help its readers grasp this major technological trend and create new system values.

Real-Time Vibration Visualization Using GPU-Based High-Speed Vision

In this study, we developed a real-time vibration visualization system that can estimate and display vibration distributions at all frequencies in real time through parallel implementation of subpixel digital image correlation (DIC) computations with short-time Fourier transforms on a GPU-based high-speed vision platform. To help operators intuitively monitor high-speed motion, we introduced a two-step framework of high-speed video processing to obtain vibration distributions at hundreds of hertz and video conversion processing for the visualization of vibration distribution at dozens of hertz. The proposed system can estimate the full-field vibration displacements of 1920 × 1080 images in real time at 1000 fps and display their frequency responses in the range of 0–500 Hz on a computer at dozens of frames per second by accelerating phase-only DICs for full-field displacement measurement and video conversion. The effectiveness of this system for real-time vibration monitoring and visualization was demonstrated by conducting experiments on objects vibrating at dozens or hundreds of hertz.

Scalable Hardware Efficient Architecture for Parallel FIR Filters with Symmetric Coefficients

Symmetric convolutions can be utilized for potential hardware resource reduction. However, they have not been realized in state-of-the-art transposed block FIR designs. Therefore, we explore the feasibility of symmetric convolution in transposed parallel FIRs and propose a scalable hardware efficient parallel architecture. The proposed design inserts delay elements after multipliers for temporal reuse of intermediate tap products. By doing this, the number of required multipliers can be reduced by half. As a result, we can achieve up to 3.2× and 1.64× area efficiency improvements over the modern transposed block method on reconfigurable and fixed designs, respectively. These results confirm the effectiveness of the proposed STB-FIR architecture for hardware-efficient, high-speed signal processing.

(Invited) 3D Electrode Architectures for High Power and High Energy Lithium-Ion Battery Operation - Recent Approaches and Process Upscaling

During the next decades, combustion driven cars will be completely replaced by electrical vehicles (EVs) and it seems quite obvious that liquid electrolyte lithium-ion batteries (LIBs) will be the dominating energy storage system for the next at least 5 to 10 years. As a consequence, in Europe numerous Gigafactories have recently been planned with this state of technology. However, the current lithium-ion battery technology suffers so far from some restrictions like the inability to combine high power and high energy operations at the same time. This limitation is mainly attributed to the cathode architecture and respective mass loading. In addition, the further demand for a significantly enhanced fast charging mainly requires an optimization of the anode design flanked by a high areal capacity. Advanced 3D electrode architectures based on a thick film electrode concept seem to be the most promising approach to overcome the current limitations in battery performances. However, respective technology innovations need to provide a high compatibility grade to existing manufacturing routes in order to enable the required integration in existing and planned factories. For so-called “generation 3” materials, i.e., nickel-rich lithium nickel manganese cobalt oxide (NMC) cathode and silicon-based anode materials, structuring technologies using cutting edge ultrafast high power lasers, are being developed in order to manufacture 3D electrode architectures with high areal capacity. Multibeam laser processing using diffractive optical elements and dual scanner approaches were established in order to enable high processing speeds in roll-to-roll electrode handling systems. The technology readiness level (TRL 6) is demonstrated for pouch cells geometries. For water-based NMC 622 and silicon-graphite composites the laser structuring process was developed. Different structures including hole, grid, and line patterns, were studied regarding their impact on electrochemical performances such as high-rate capability and cell lifetime. Lithium concentration profiles of unstructured and structured electrodes were studied post mortem using laser-induced breakdown spectroscopy (LIBS) in order to evaluate lithium intercalation/deintercalation efficiencies and detect possible cell degradation processes. In comparison to unstructured electrodes, 3D electrodes could hereby always be identified as superior: unstructured thick film electrodes show a significant drop in capacity retention for high power operation and tend to form hot spots acting as starting point for cell failure. The upscaling process is flanked by a further improvement of electrode design. For this purpose very recently laser induced forward transfer (LIFT) is applied as printing technology to draw new concepts for sophisticated model electrode architectures with advanced electrochemical performances. Finally, the micro-/nano-scaled texturing of current collectors and separator material is discussed as further possible approaches for boosting the electrochemical performances of LIB pouch cells.

THE ROLE OF DOMESTIC ENGINEERING PRODUCTION IN MODERN CONDITIONS

An algorithm for implementing the technology for manufacturing high-quality and accurateengineering products from hard-to-cut materials based on modern CAD/CAE/CAM/CAPP systems isconsidered. The features of processing hardened steels are given. The prospects of the energy approachfor determining the area of existence of technological modes of high-speed processing of materials aresubstantiated. The dependences of changes in physical parameters on the increase in cutting speed aregiven

A Low-Latency RDP-CORDIC Algorithm for Real-Time Signal Processing of Edge Computing Devices in Smart Grid Cyber-Physical Systems.

Smart grids are being expanded in scale with the increasing complexity of the equipment. Edge computing is gradually replacing conventional cloud computing due to its low latency, low power consumption, and high reliability. The CORDIC algorithm has the characteristics of high-speed real-time processing and is very suitable for hardware accelerators in edge computing devices. The iterative calculation method of the CORDIC algorithm yet leads to problems such as complex structure and high consumption of hardware resource. In this paper, we propose an RDP-CORDIC algorithm which pre-computes all micro-rotation directions and transforms the conventional single-stage iterative structure into a three-stage and multi-stage combined iterative structure, thereby enabling it to solve the problems of the conventional CORDIC algorithm with many iterations and high consumption. An accuracy compensation algorithm for the direction prediction constant is also proposed to solve the problem of high ROM consumption in the high precision implementation of the RDP-CORDIC algorithm. The experimental results showed that the RDP-CORDIC algorithm had faster computation speed and lower resource consumption with higher guaranteed accuracy than other CORDIC algorithms. Therefore, the RDP-CORDIC algorithm proposed in this paper may effectively increase computation performance while reducing the power and resource consumption of edge computing devices in smart grid systems.

Fully Automated Directional Drilling Used on the Norwegian Continental Shelf

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 204016, “Fully Automated Directional Drilling Is Now a Reality: An Example From the Norwegian Continental Shelf,” by Jorge Heredia, SPE, Julien Marck, SPE, and Sara Heller, Halliburton, et al. The paper has not been peer reviewed. _ This paper presents an automated directional-drilling process executed on a commercial well in the Norwegian sector of the North Sea, where an intelligent rotary-steerable system (RSS) completed a well section in a single run with all drilling commands automatically computed, optimized, and downlinked by a drilling-automation platform. The section was complex, consisting of two intervals requiring steering in three dimensions separated by a tangent section. Directional-drilling engineers onshore supervised the operation remotely. No override was required, and the automated system was able to drill the entire section while sending steering decisions automatically. Advances in Drilling Automation Two primary automation controllers that were used in recent steering-automation successes on the Norwegian Continental Shelf are discussed in the complete paper. Recent advancements in RSS technologies use downhole sensors, high-speed processors, and survey packages to provide the backbone for an autonomous downhole navigation system. This type of development enables an automated closed-loop attitude-hold feature. Once configured, the only required downlinks correct trajectory, therefore reducing the total number of downlinks required to steer per section and creating a consistent wellbore quality between wells. This system was applied during the tangent portion of the well discussed in the complete paper. A second development is that of steering automation and advisory systems for deviated steering applications. These systems respond to real-time information from surface systems, including continuous inclination and azimuth measurements from downhole sensors and surface-drilling parameters. The real-time information then is fused with a physics-based digital twin model of the bottomhole assembly (BHA) to produce a calibrated steering model. Based on this hybrid model, the system combines control and optimization algorithms to reconstruct the borehole geometry between the last-available survey and the borehole depth and then provide recommendations for steering magnitudes and direction to meet drilling objectives while accounting for safety margins and drilling constraints. Benefits of the advisory system include reducing human error by removing unnecessary intervention, and automating calculations based off continuous real-time sensor information as opposed to the conventional method of requiring manual interpretation of data. The presented results illustrate the effect of these integrated systems on the improvement of borehole quality and placement and how the controller overcomes typical field situations successfully, such as challenging formations and wellbore conditions and changes in targets and steering objectives. The drilling-automation platform allows the directional-drilling operator to remain onshore in a remote drilling center as opposed to being on the offshore platform. Previous challenges and risks associated with holding operations remotely are being left behind as Internet bandwidth increases and no requirement exists to rely simply on phone and email correspondence; instead, onshore operators can view computers and cameras located at the rigsite in real time.

Heliconical Cholesterics Endows Spatial Phase Modulator with an Electrically Customizable Working Band (Advanced Optical Materials 19/2022)

Orthogonal manipulation of multi-dimensional parameters of light is urgently desired in high-speed processing and reliable transmission of massive information. In article number 2201088, Zhi-Gang Zheng, Yan-Qing Lu, Wei Hu and co-workers present a heliconical cholesterics-based spatial phase modulator with electrically customizable working frequency. The device simultaneously manipulates the spatial phase and wavelength/frequency of light via photoaligning the initial orientation of the liquid crystal and electrically varying the pitch of the heliconical superstructure, respectively. It supplies a platform for multidimensional planar optics that may upgrade existing optical informatics.

Adaptive nonlinear motion parameters estimation algorithm for digital twin of multi-link mechanism motion trajectory synthesis

Monitoring systems of automated production lines requires high accuracy and processing speed of acquired data. Nowadays digital twin technologies are rapidly developing as part of Industry 4.0. Digital twin is a virtual representation of a physical system that mimics the behaviour of a real object, and is used in real-time control, monitoring and disturbance prediction, without influence on a real object. Digital twin is being used in many fields of application such as: healthcare, manufacturing, education, city development, etc. Nonetheless, despite the rising popularity of digital twin researches, there is no basic approach to digital twin synthesis. Mostly, in state of the art articles, systems with known parameters are considered. In this paper, approach to development of digital twin, based on internal model for multi-link mechanisms with unknown motion parameters, is presented. Described approach intended to ease the task of production line monitoring and extend digital twin technology application field. In this article adaptive controller design, based on internal model, is presented, theoretical explanations of design process are provided, and application of the control algorithm in the task of multi-link mechanism motion trajectory parameters estimation is described. In this work the experimental synthesis of digital twin for Kuka youBot manipulator based on presented approach in real time is described. Adaptive motion parameters estimation was made for two links of the manipulator for the sake of confirmation of presented approach usage in the task of digital twin for systems with unknown parameters. Motion trajectory parameters of the robot links were defined manually with the use of chaotic generators to estimate the accuracy of the adaptive control system. This approach was used in order to calculate the error of reference tracking by comparing the control signal for digital twin with the reference exogenous input for manipulator links. As the results of the experiment, the graphs of the error reference tracking for both links are presented. As the goal of the experiment, the convergence of reference tracking error to the field [–0.005, 0.005] radian was set, and as can be seen from graphs this goal was achieved. There is a small disturbance of the error convergence on the graphs within the desired field which was caused by noised measurements and delays of the chosen modelling environment real-time simulations. In the conclusion of this paper, further work to reduce the influence of mentioned causes is described. The results of this paper can be used in further digital twin technology researches. Presented approach can be implemented in robots remote control tasks, production lines technical condition monitoring and in general motion trajectory parameters estimation tasks for multi-link mechanisms