Generate Control Signals Research Articles

Tactile simulation of textile fabrics: Design of simulation signals with regard to fingerprint

This study describes a systematic approach to generate control signals of a tactile simulator to render the touch of textile fabrics. As a friction modulation tactile surface is used, control signals were generated from tribological measurements on real surfaces. Forces were acquired from an artificial finger, with a texture mimicking fingerprints. Then the signals are processed in frequency domain and send as control signal to the tactile stimulator. This paper focusses on the potential benefits of including the fingerprint information in the simulation of fabrics for achieving realistic tactile perception. A sensory analysis with 36 participants was carried out using the generated control signals, and results show a better discrimination without fingerprint information.

High Precision Control System for Micro-LED Displays

This paper proposes a Field Programmable Gate Array (FPGA)-based control system to implement micro-light-emitting diode (micro-LED) real-time display. The control system includes the interface control, video processing, memory management, image data transmission, control signal generation and correction. Then, we implement the micro-LED real-time display via memory management. We propose the brightness correction to achieve high grey-scale and high uniformity display. The LEDs are mounted on the glass substrate prepared using low-temperature polysilicon (LTPS) technology, and then we find the 24 × 46 pixels micro-LED panel. And the control system has been successfully applied to the panel of glass-based micro-LED displays. A new grey control method is proposed in this work, which can effectively improve the refresh rate of the micro-LED displays. The high grey-scale refresh rate is 2100 Hz, and the low grey-scale refresh rate is 300 Hz. The uniformity of the panel is increased to 85% after brightness correction.

Design and Experimental Testing of an Overhead Rail Automatic Variable-Distance Targeted Spray System for Solar Greenhouses

Crop cultivation in solar greenhouses is affected by issues such as low levels of automation in spraying machinery, inefficient spraying, and a lack of suitable spraying equipment for vertically cultivated crops, all of which are in urgent need of resolution. To address these problems, this paper proposes a suspended-rail automatic variable-distance targeted spray system. The rated working speed of the spray system is 0.3 m/s, and the rated working pressure is 0.3 MPa. This system achieves precise spraying of crops at varying heights by dynamically adjusting the position of the spray nozzle. To ensure accuracy in spraying, the system employs a laser ranging sensor for real-time measurement of crop positions and spraying distances. Combined with a parameter processing scheme, the system generates control signals to adjust the operation of the electric push rod and electromagnetic valve, thereby dynamically adjusting the spraying distance and timing. Using vertically cultivated potted peppers as experimental subjects, this study compares the performance of fixed- and variable-distance spraying modes. The results indicate that, compared to the fixed-distance mode, the automatic variable-distance mode increases pesticide adherence by 16.65% and reduces pesticide usage by 29.58%. The proposed suspended-rail automatic variable-distance targeted spray system offers an effective technical solution for the precise spraying of vertically cultivated crops in solar greenhouses and thus contributes to improved pesticide utilization efficiency, reduced pesticide residue, and lower environmental pollution.

Quadruple spherical tank systems with automatic level control applications using fuzzy deep neural sliding mode FOPID controller

The premier goal of this research is to develop the Fuzzy Deep Neural Sliding Mode Fractional Order Proportional Integral Derivative (FDN-SM-FOPID) controller system for controlling liquid in quadruple spherical tank systems. This is used in non-linear spherical systems to control the level of liquid in real time. These models' dynamics allow for a more accurate identification of the spherical tank system that generates control signals from liquid samples obtained at reference levels. However, because the system is susceptible to outside disturbances, error minimization is not done. Therefore, it requires the addition of a special controller to lessen this flaw. The suggested Deep Neural Fuzzy model's six-layered network is optimized using the back-propagation method. As a result, the system's efficient training reduces offset model errors, steady state errors, and unmeasured disturbances. The liquid level is maintained and controlled by this neural intelligence system, which meets the necessary design requirements such as no overshoot, time constant, less settling and rise time, which is used in various platforms. The FOMCON toolbox in MATLAB software is used for research simulation work. The chemical industry, wastewater treatment, the aerospace industry, and the pharmaceutical industry have all employed the suggested quadruple spherical tank system to test its practicality. The experimental and simulation results are demonstrated by a real-time liquid control experimental setup.

Гравитационная транспортная система: принципы построения и управления

The paper considers the principle of constructing a gravitational transport system designed for container transportation of the technological materials. It proposes a scheme of the transport system providing the container shuttle motion between the stations. A scheme is developed, and description of the stations operation principle is presented being a part of the transport system; the compressed air energy is used there to provide transport container with the potential energy ensuring its motion along the transport route under the gravity influence. The proposed station scheme makes it possible to consider the station as a functionally complete module forming the basis for possible development of the extended transport systems with various configurations. An algorithm for the station functioning was developed that implemented the processes of sending and receiving a container. A microprocessor system for managing the station mechanisms is proposed, which controls the sensor signals state and generates control signals for the compressed air distributors. A computer model of the control system was designed and developed to debug algorithms for controlling the transport system stations. The considered schemes and algorithm are intended to develop the technological transport lines.

Development of a gating grid driver of TPC for exotic beam experiments

The Multi-purpose Time Projection Chamber (TPC) for nuclear AsTrophysical and Exotic beam experiments (MATE) is being upgraded for the decay and active target experiments at the Heavy Ion Research Facility in Lanzhou (HIRFL). We have developed a gating grid driver to control the transitions between the closed and open states of the gating grid of the MATE-TPC to detect interesting rare decay events from a large amount of implanted ions. The gating grid driver is mainly composed of a digital control unit and a high-voltage switch unit. The digital control unit responds to the external trigger and generates control signals for the operation of the high-voltage control part based on the presetting instruction. The high-voltage switch unit is connected to two negative high voltages with different values and changes the voltages of neighboring wires of the gating grid based on the request for closing or opening the gate. A 500 ns switching time of the gating grid driver has been achieved from the closed to open state. The duration of the open state can be adjusted from 1 µs to 99 ms based on the experimental requirements. This gating grid driver can be used in a particle detector with a high voltage bias of up to ± 3000 V.

Life-Aware Operation of Battery Energy Storage in Frequency Regulation

The rapid growth of renewable generation in power systems imposes unprecedented challenges on maintaining power balance in real time. With the continuous decrease of thermal generation capacity, battery energy storage is expected to take part in frequency regulation service. However, accurately following the automatic generation control (AGC) signal leads to more frequent switching between charging and discharging states, which may shorten battery life. Because battery life is a consequence of long-term operation depending on the depth of discharge, it is difficult to model battery health in frequency regulation problems. This paper establishes an online operation policy in response to the real-time AGC signal considering battery health. Based on the empirical relation between cycling number and depth of discharge, a cost function is suggested to approximate the impact of charging-discharging action on battery life in the long run. Then, Lyapunov drift-plus-penalty technique is employed to derive an explicit online policy compromising the revenue of frequency regulation and battery life without requiring future AGC data. The offline operation problem after knowing the entire sequence of AGC signal is cast as a difference-of-convex program and solved by a sequential convexification algorithm. The gap between the offline and online optimum is shown to be a constant, which quantifies the value of knowing future information. Case studies based on AGC data from the PJM market validate the proposed method.

Kinematics-Based Motion-Force Control for Redundant Manipulators With Quaternion Control

Motion-force control of redundant manipulators is universally regarded as a pivotal issue in industrial manufacturing, especially for the processing of precision instruments. This paper proposes a kinematics-based motion-force control (KBMFC) scheme for redundant manipulators, which is driven by joint velocity commands and different from the dynamics-based methods. Specifically, the force and motion are modeled and decoupled in the end-effector frame with the help of a stiffness coefficient. To control the orientation of the force, a quaternion control equation is designed by combining the rotation matrix and neural dynamics method. Different from traditional motion-force control methods, the proposed scheme is constructed as quadratic programming with the corresponding recurrent neural network (RNN) solver derived, which considers the kinematic optimization index and joint constraints. According to the generated control signals, a redundant manipulator is able to accurately fulfill the hybrid control of motion and force with the desired quaternion, which is intuitively confirmed by simulations and experiments. <i>Note to Practitioners</i>&#x2014;This paper is motivated by the deficiencies that restrict the real-world applications of the motion-force control of redundant manipulators. On the one hand, most existing motion-force control schemes are implemented under the framework of dynamics, which inevitably leads to some kinematics-related defects. On the other hand, the latest kinematics-based techniques introduce an admittance control to achieve motion-force control. However, they model the force in the Z-axis of the base coordinate while the motion planning is limited in the X-Y plane, which dramatically reduces real-world applications. In this paper, the deformation force is designed in the end-effector frame, and a quaternion control technology of the end-effector is developed. Such a scheme can realize the real-time control of the orientation and magnitude of the force while ensuring trajectory tracking. In addition, the introduction of optimization indexes and joint constraints dramatically improves the functionality of the proposed scheme. Finally, the contributions of this paper are verified through simulations, experiments and comparisons. This work proposes a feasible framework for the motion-force control and orientation control of redundant manipulators.

CONTROL SYSTEM OF THE ELECTRIC DRIVE OF THE LOOP HOLDER OF THE FINISHING GROUP OF THE HOT ROLLING MILL, WHICH IMPLEMENTS CONTROL AND FORCING OF THE ELECTRIC DRIVE MOMENT

The operation of the DC electric drive of the loop holder installed on the hot rolling mill between the stands of the finishing group, which is part of the SARN with the indirect principle of metal tension control, which generates control signals based on the control of the specific tension of the strip passing between two stands, is considered. It is shown that the SARN action algorithm is based on taking into account the impact on the strip of the auxiliary mechanism – the loop holder, the frame of which must be rotated to the optimal angle. The conditions are described under which the looper is in an equilibrium state, when the moment of the electric motor balances the moment of resistance on its shaft, determined by the force arising due to the tension of the strip. It is shown that the high-speed electric drive of the looper, which is in the steady braking mode for most of the cycle time and creates a braking torque, at the moment the strip enters the interstand gap, should provide a short-term forcing of the moment for the movement of the frame, followed by a stop in the allowable zone of the angle of rotation.

FUZZY-LOGIC MODELING OF TEMPERATURE REGIMES IN THE PROCESSES OF RADICAL SUSPENSION POLYMERIZATION

An approach to the synthesis of neuro-fuzzy models of temperature regimes of industrial reactors for polymer synthesis is proposed for consideration. The expediency of developing such a model is justified by its subsequent application in intelligent robust-adaptive automatic control systems as a reference model for generating control signals. The basis for constructing a fuzzy model of the reactor is an array of data obtained as a result of conducting many experiments on a physical model of a polymer synthesis reactor. Structurally fuzzy model includes three blocks of fuzzy logic. The first block is a fuzzy model of the kinetics of the polymerization process. The output of this block is a monomer conversion curve. The second block of the fuzzy model generates a curve of change in the temperature of the mixture in the reactor normalized to the range [0;1]. This is possible due to the fact that the shape of the temperature change curve depends only on the moment of exhibition of the gel effect, which is inherent in the processes of radical polymerization. This point can be unambiguously determined from the monomer conversion curve. The third block of the fuzzy model calculates the value of the scaling factor based on the current flow rate of the coolant, as well as the set value of the water modulus and the temperature regime in the reactor. After calculating this coefficient, it is multiplied by a normalized curve and the value of the specified temperature regime is added, obtaining at the output the final curve of temperature change in the reactor. The block structure of the proposed fuzzy model is its essential difference from possible analogues and its key advantage. Due to this structure of the model, it is possible to replace, if necessary, some of its elements in order to obtain the possibility of modeling the processes of radical polymerization of different monomers. For citation: Lopatin A.G., Brykov B.A. Fuzzy-logic modeling of temperature regimes in the processes of radical suspension polymerization. ChemChemTech [Izv. Vyssh. Uchebn. Zaved. Khim. Khim. Tekhnol.]. 2023. V. 66. N 6. P. 123-129. DOI: 10.6060/ivkkt.20236606.6682.

A Comprehensive Overview on Performance of Cascaded Three Tank Level System using Neural Network Predictive Controller

A Neural Network Predictive Controller (NNPC) is a deep learning-based controller (DLC) that uses artificial neural networks (ANN) to predict the future behavior of a system and accordingly control its outputs. In this paper, an NNPC was used to predict the level of the three cascaded tank and then adjust the inputs as flow rate to maintain the desired level in the tank. A three-tank level system is a system consisting of three interconnected tanks used to store liquids. To achieve the desired level, the NNPC first collects data on system behavior, including inputs and outputs, and uses this data to train the neural network. The trained network was then used to make predictions about the future level of each tank and to generate control signals to adjust the inputs as needed. NNPC also incorporates feedback from the system to continuously refine its predictions and improve its control performance over time. The mean squared error (MSE) of different backpropagation training algorithms available in MATLAB deep learning toolbox were evaluated and presented. Based on the MSE and best validation, Levenberg Marquardt algorithm were used in NNPC controller for further step response tracking. Different performance metrics were evaluated and presented.

ROS-Based Autonomous Navigation Robot Platform with Stepping Motor

Indoor navigation robots, which have been developed using a robot operating system, typically use a direct current motor as a motion actuator. Their control algorithm is generally complex and requires the cooperation of sensors such as wheel encoders to correct errors. For this study, an autonomous navigation robot platform named Owlbot was designed, which is equipped with a stepping motor as a mobile actuator. In addition, a stepping motor control algorithm was developed using polynomial equations, which can effectively convert speed instructions to generate control signals for accurately operating the motor. Using 2D LiDAR and an inertial measurement unit as the primary sensors, simultaneous localization, mapping, and autonomous navigation are realised based on the particle filtering mapping algorithm. The experimental results show that Owlbot can effectively map the unknown environment and realise autonomous navigation through the proposed control algorithm, with a maximum movement error being smaller than 0.015 m.

Development of a High-Voltage Pulsed Electric Field Sterilization Power Supply Using a New Topology Circuit

Traditional thermal sterilization technology is easy to implement and safe, but it will destroy food nutrition and change food taste. Therefore, people began to turn their attention to non-thermal sterilization. High-voltage pulsed electric field sterilization technology is one of them; it has attracted much attention because of its high efficiency and little damage to food. Different types of loads will cause serious trailing of the pulse falling edge. In view of this situation, this paper proposes a new topology circuit that combines a solid-state switch with a half-bridge Marx generator. It can be used for high-voltage pulsed electric field sterilization. By improving the structure of the classical Marx circuit, the high-voltage pulse power supply of the new topology circuit has the characteristics of steep rising edge and short falling edge delay; does not require isolation inductance or isolation resistance, which solves the isolation problem between the DC charging power supply and the high-voltage terminal; and has a good voltage-clamping function and load adaptability. The working process of the topology circuit under resistive, capacitive and inductive loads and the voltage clamping effect when the solid-state switch does not work properly in the discharge process are analyzed in detail. The power supply is composed of an adjustable DC power supply, five-stage half-bridge Marx generator and control protection circuit. A field programmable gate array (FPGA) is used as the controller to generate control signals, and optical fiber isolation is used to provide control signals for the main loop. The power supply can output a high-voltage square wave pulse with a voltage amplitude of 10 kV, maximum pulse number of 1000 per second, maximum pulse width of 20 μs, pulse rise time of smaller than 300 ns and short pulse drop time, and the repeated voltage amplitude, frequency and pulse width are adjustable, which can meet the requirements of a high-voltage pulse sterilization experiment.

Precision Hall Effect magnetometer.

The article presents a Hall effect magnetometer for use in a desktop Electron Paramagnetic Resonance spectrometer with a permanent magnet system and scanning coils. High accuracy and long-term stability at a small size and low cost are achieved through the use of digital signal processing, sequential data filtering in the time and frequency domains, as well as digital correction of raw data based on calibration information. The exciting current of the Hall sensor has the form of an alternating-signsquare wave formed by a high-speed H-bridge powered by a stable direct current. Generation of control signals, time selection of data, and their accumulation are performed using Xilinx Field-Programmable Gate Array Artix-7. MicroBlaze embedded 32-bit processor is used to control the magnetometer and interface with adjacent levels of the control system. Taking into account the individual characteristics of the sensor, including the offset voltage, the nonlinearity of the magnetic sensitivity, and their temperature dependences, is carried out by correcting the data obtained by calculating a polynomial depending on the raw magnitude of the field induction and the temperature of the sensor. The polynomial coefficients are individual for each sensor, are determined once during the calibration process, and are stored in the dedicated Electrically Erasable Programmable Read-Only Memory. The magnetometer has a high resolution of 0.1 µT and an absolute measurement error of not exceeding 6 µT.

Throttle-Free Booster DC/DC Converter

The results of the analysis of the features of the charge pumping process in devices with switched capacitors, as well as the features of switching processes in transient operating modes, are presented. The methods by which a high efficiency of charge pumping is achieved are considered. Circuit modeling made it possible to refine the characteristics of processes, minimize conversion losses, formulate recommendations for choosing the parameters of converter elements, and generating control signals.

A High-Power Solar PV-fed TISO DC-DC Converter for Electric Vehicle Charging Applications

In this paper, a two-input, single-output (TISO) DC-DC converter for electric vehicle charging applications with solar photovoltaic (PV) as one of the sources is discussed. A novel, simple, and effective control strategy with maximum power point tracking (MPPT) to maximize power from PV while maintaining a constant bus voltage is proposed. A 100 V, 100 W TISO DC-DC converter is designed and comprehensive simulations are conducted under different conditions. The system characteristics are validated by comparing the results with a conventional P&amp;O algorithm and multiple step size P&amp;O algorithm. The proposed control strategy can precisely generate control signals to track MPPT while maintaining the bus voltage by controlling the output of a fixed DC source according to the changes in PV generation. The overall efficiency of the proposed approach is 98.67%, and the average output voltage is 99.09 V under selected conditions. The overall average output voltage ripple is 0.22% with the proposed approach, while it is 2.91% and 1.55% with the conventional P&amp;O and multiple step size P&amp;O MPPT techniques, respectively. Further, a 500 V, 17 kW high-power converter is designed and a simulation is carried out. The high-power converter provides an average output voltage of 496.92 V with an overall efficiency of 98.72%, and the average output voltage ripple is 0.16%. The results obtained from the simulation under the selected conditions lead to the conclusion that the converter has better efficiency and less variation in the output voltage at higher power levels with the proposed control technique.

Design and implementation of electrical engineering experiment based on the Arduino platform

Arduino platform is a new hardware and software combination platform that is widely used, flexible, easy to operate, and rapidly developing. In this paper, the design and implementation of the DC chopper circuit were conducted based on the Arduino platform. Firstly, the power signal and trigger signal are output in the form of programming on the Arduino platform, and the rest of the circuit is built on the breadboard in the form of hardware. Finally, the design waveform is obtained. This paper introduces the basic working principles of four power conversion circuits, conducts circuit simulation on MATLAB software and obtains the ideal output waveform, and uses C language programming to trigger control signal generation, generates corresponding electrical signals through compilation and USB wire transmission to Arduino controller, and builds relevant circuits. This paper makes use of the advantages of the breadboard, fully combines the theoretical knowledge and circuit connection, and finally observes the output waveform through an oscilloscope, and compares the waveform of the actual circuit with the simulation results of MATLAB.

Generation and Switching of Human Gait Control Signals by Hardware CPG Model Mimicking the Brainstem Spinal Projection System

Generation and Switching of Human Gait Control Signals by Hardware CPG Model Mimicking the Brainstem Spinal Projection System

Optimal Frequency Regulation Using Packetized Energy Management

Packetized Energy Management (PEM) is a demand dispatch scheme that can be used to provide ancillary services such as frequency regulation. In PEM, distributed energy resources (DERs) are granted uninterruptible access to the grid for a pre-specified time interval called the packet length. This results in a down ramp-limited response in PEM for DERs that can only consume power from the grid. In this work, a linearized virtual battery model of PEM is provided that is capable of predicting the down ramp-limited output of PEM and is used in a model predictive control (MPC) framework to improve the performance of PEM in tracking an automatic generation control (AGC) signal. By performing statistical analysis on the AGC regulation signal, PJM Reg-D, an autoregressive moving average (ARMA) model is derived as a predictor for the MPC-based precompensator. Finally, as an alternative to MPC, it is shown that by varying the packet length as a function of time, for example through packet randomization, frequency regulation can be improved under PEM.

COMPONENTS OF A SYSTEM FOR AUTOMATIC DETECTIONOF A ZONE OF INTEREST IN IMAGES OBTAINED FROM A UAV

To reduce the load on the UAV operator during long-term search and rescue missions, an on-board automatic system that generates control signals for positioning an additional video camera with a narrow field of view is considered. The re-quirements for the system of automatic detection of the area of interest are defined. Various methods for detecting objects in images are considered, analyzed and compared. Software and hardware tools are discussed, which are advisable to use in the preparation and conduct of experimental studies.