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The manufacturing process for corrugated paper products is usually mass production and batch-by-batch production. Therefore, a high-speed mass production is required. Because the conveyer speed of the production line in a corrugated paper plant is very fast, unwanted material loss or even process interruption may occur during the cutting or clipping process if the corrugated paper on the conveyer is slanted. Hence, the paper alignment on a conveyer is important and necessary. In this study, we install photo-couples at both edges directly over the conveyer path to detect whether or not the corrugated paper is slanted from the number difference between non-activated photo-couples of the two edges. The deviated angle is calculated through a computer program using the detected information, and a servomotor-driven wheel aligns the paper in accordance with the calculated angle. This work reduces the material waste and promotes the production reliability and utility rate of the material for a corrugated paper plant. [ABSTRACT FROM AUTHOR]

To improve dynamic performance and steady-state accuracy of position leap control of the direct current (DC) servo motor, a fuzzy inference system (FIS) enabled artificial neural network (ANN) feedforward compensation control method is proposed in this study. In the method, a proportional-integral-derivative (PID) controller is used to generate the baseline control law. Then, an ANN identifier is constructed to online learn the reverse model of the DC servo motor system. Meanwhile, the learned parameters are passed in real-time to an ANN compensator to provide feedforward compensation control law accurately. Next, according to system tracking error and network modeling error, an FIS decider consisting of an FI basic module and an FI finetuning module is developed to adjust the compensation quantity and prevent uncertain disturbance from undertrained ANN adaptively. Finally, the feasibility and efficiency of the proposed method are verified by the tracking experiments of step and square signals on the DC servo motor testbed. Experimental results show that the proposed FIS-enabled ANN feedforward compensation control method achieves lower overshoot, faster adjustment, and higher precision than other comparative control methods. [ABSTRACT FROM AUTHOR]

This paper presents an adaptive probabilistic recurrent Takagi-Sugeno-Kang fuzzy neural PID controller for handling the problems of uncertainties in nonlinear systems. The proposed controller combines probabilistic processing with a Takagi-Sugeno-Kang fuzzy neural system to proficiently address stochastic uncertainties in controlled systems. The stability of the controlled system is ensured through the utilization of Lyapunov function to adjust the controller parameters. By tuning the probability parameters of the controller design, an additional level of control is achieved, leading to enhance the controller performance. Furthermore, it can operate without relying on the system's mathematical model. The proposed control approach is employed in nonlinear dynamical plants and compared to other existing controllers to validate its applicability in engineering domains. Simulation and experimental investigations demonstrate that the proposed controller surpasses alternative controllers in effectively managing external disturbances, random noise, and a broad spectrum of system uncertainties. • We propose an adaptive probabilistic recurrent TSK fuzzy neural PID controller. • The Lyapunov stability criterion is used to update the proposed controller parameters. • The proposed controller is applied practically for controlling a servo motor. [ABSTRACT FROM AUTHOR]

For enhancing the load torque synchronization performance of dual‐driven systems, the inherent coupling effect between the parallel axes is analyzed first and could be described as two distinct components of the synchronous error. Thus, the feedforward‐feedback composite synchronous control scheme is proposed in this paper to eliminate these desynchronization factors. Secondly, the selection of synchronization objectives such as speeds, positions or currents of parallel axes is analyzed, which may not accurately reflect the actual load desynchronization due to mismatch dynamics. To overcome this drawback, the synchronous feedback controller is modified by incorporating a load torque observer, which can provide good adaptation to modelling errors, disturbances and eliminate the load desynchronization effectively. Simulation and experimental results demonstrate significant improvement in load torque synchronization performance achieved by the proposed control scheme. [ABSTRACT FROM AUTHOR]

The development of science and technology has experienced such rapid growth, thus encouraging humans to try to overcome all problems that arise around them and ease the work around the environment through automatic control systems. One of the technologies currently being developed is the Arduino microcontroller. Based on the problems often experienced by students when leaving clothes to dry in the dormitory. If it rains or bad weather, it can be a problem if you do not have time to lift the clothesline so that dry clothes become wet with rainwater when there are no dorm residents because they are on campus. Given these problems, the author designed an automatic drying room prototype using a rain sensor and light sensor based on an Arduino microcontroller. The components used are a drying room and roof, a light sensor and water sensor as input, an Arduino microcontroller, breadboard and jumper cables, a power bank as a processor, and a servo motor and LED lights as output. A servo motor automatically moves the roof of the clothes' drying room, and the LED lights turn on, according to input from the light sensor and rain sensor, according to the conditions received by the sensor. [ABSTRACT FROM AUTHOR]

This study proposes a high-resolution rotation-measuring system for miniaturized MEMS ultrasonic motors using tunneling magnetoresistance (TMR) sensors for the first time. Initially, the architecture and principle of the rotation-measuring system are described in detail. Then, the finite element simulation is implemented to determine the miniaturized permanent magnet's residual magnetization, dimensions, and TMR sensor position. Finally, the experiments are implemented to evaluate the performance. Using calibration based on a high-precision servo motor, it is found that the relationship between the output and rotational angle is highly linear and immune to the rotor's out-of-plane movement. Meanwhile, the angle-detecting resolution is higher than 0.1°. After the calibration, the continuous rotation of the MEMS ultrasonic motor is tested. It is found that the angle testing result varies with a period close to 360°, which indicates that the rotation-measuring system has successfully detected the motor's rotation. [ABSTRACT FROM AUTHOR]

With the rapid development of the manufacturing industry toward intelligence and flexibility, traditional mechanical presses are unable to meet the increased stamping requirements due to the difficulties in achieving variable speed control and changing slide motion trajectories. Servo presses, driven directly by servo motors, can realize the flexible control of press movement and have become the trend in the industry for future development. The independent research and development of servo press control systems has become a popular topic and challenge in the domestic press industry. This paper proposes a new type of press transmission mechanism suitable for high-precision stamping, analyzes the working principle of its transmission mechanism, and provides a detailed analysis and discussion on the main research methods of fuzzy intelligent control for servo presses, including fuzzy model and basic control algorithms, fuzzy modeling and control of nonlinear systems, fuzzy predictive control, and stability analysis of fuzzy control systems. Based on the principle of the control scheme, a closed-loop control system block diagram and mathematical model for servo high-precision presses are established. Taking the physical prototype parameters of the STSZG1-250 as an example, the control system is dynamically simulated and verified using Simulink modules. Finally, their role and effects in intelligent control, and prospects for the development of fuzzy intelligent control, are discussed. [ABSTRACT FROM AUTHOR]

Multi-motor servo systems are widely used in industrial control. However, the single-core microprocessor architecture based on the microcontroller unit (MCU) and digital signal processor (DSP) is not well suited for high-performance multi-motor servo systems due to the inherent limitations in computing performance and serial execution of code. The bus-based distributed architecture formed by interconnecting multiple unit controllers increases system communication complexity, reduces system integration, and incurs additional hardware and software costs. Field programmable gate array (FPGA) possesses the characteristics of high real-time performance, parallel processing, and modularity. A single FPGA can integrate multiple motor servo controllers. This research uses MCU + FPGA as the core to realize high-precision multi-axis real-time control, combining the powerful performance of the MCU processor and the high-speed parallelism of FPGA. The MCU serves as the central processor and facilitates data interaction with the host computer through the controller area network (CAN). After data parsing and efficient computation, MCU communicates with the FPGA through flexible static memory controller (FSMC). A motor servo controller intellectual property (IP) core is designed and packaged for easy reuse within the FPGA. A 38-axis micro direct current (DC) motor control system is constructed to test the performance of the IP core and the heterogeneous embedded platforms. The experimental results show that the designed IP core exhibits robust functionality and scalability. The system exhibits high real-time performance and reliability. [ABSTRACT FROM AUTHOR]

In this paper, a gap nonlinear compensation strategy is proposed for the full closed-loop control structure of non-direct-drive servo motor systems. Firstly, an improved deadband model containing the initial value of the gap is proposed, and two gap amplitude identification methods, namely, incremental torque and velocity difference integral, are compared. Then, for the full closed-loop structure, based on the describing function and the stability theory of the nonlinear system, the limit-loop oscillating frequency and the influencing factors are predicted, which are related to the system control stiffness and independent of the gap amplitude; finally, the state-feedback control is proposed, and the feedback coefficients are designed by using the pole configuration, making the system a pseudo-linear system. Simulation and experimental verification show that the method can suppress the limit loop oscillation, attenuate the system shock, and have a certain robustness. [ABSTRACT FROM AUTHOR]

Copyright of Machine Tool & Hydraulics is the property of Guangzhou Mechanical Engineering Research Institute (GMERI) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Soft robots and wearable technologies benefit significantly from stretchable batteries, yet the rigid nature of high‐capacity electrodes creates large trade‐offs in battery performance and stretchability. This study introduces a new approach for realizing stretchable batteries by allowing the electrodes to slide along a stretchable electrolyte. When the sliding‐electrodes battery is stretched, the forces are transmitted through the hydrogel electrolyte and elastomeric enclosure, while the rigid electrodes slide relative to the hydrogel to maintain interfacial contact. The sliding‐electrodes approach allows 100% of the unstretched battery area to be covered by thick electrodes so that the battery areal capacity and power are improved by up to 10X of prior stretchable designs. Three metal‐air batteries achieve areal capacities of up to 104 mWh cm−2. Further mechanical testing, electrochemical characterization, and integration into soft robotic systems demonstrate the potential of these stretchable batteries in practical applications. The sliding‐electrodes battery can stably power multiple servo motors and sensing circuits under stretching, twisting, bending, and after impact. [ABSTRACT FROM AUTHOR]

The permanent magnet linear motor (PMLM) systems are widely applied in various engineering fields. However, the state inequality constraints and uncertainties of parameters and unknown external disturbances need to be further explored. In this article, first, a state transformation method is proposed for converting bounded states to unbounded states. As a result, the output state of system is limited within the expected boundary constraint. Then, a new control strategy is constructed. This strategy can ensure that the controlled system with uncertainties is uniformly bounded and uniformly ultimately bounded. Finally, the effectiveness of the controller and the state transformation method are verified through simulation of PMLM system. The inequality constraints of the output state are satisfied, and the system performance is improved. [ABSTRACT FROM AUTHOR]

This research paper presents the development and analysis of a multifaceted smart grid prototype. It combines various technologies for the smart grid operation. The first technology is environmental analysis of smart grid and solar panel cleaning. Secondly, radio-frequency identification (RFID)-based security and access control system has been integrated for smart grid. The third component is internet of things (IoT)-based energy monitoring and load management. For environmental analysis sensors such as temperature, humidity, light-dependent resistor, and flame sensors are connected to a NodeMCU controller for real time monitoring. Moreover, IoT based solar cleaning system is developed in the form of prototype with the help of Blynk and servo motor. The second component of prototype is smart security system which is developed with the help of Arduino and RFID module to facilitate secure access control. The third part of prototype employs voltage and current sensors with an ESP32 microcontroller and the Blynk application for real-time energy consumption analysis. This setup enables remote monitoring of voltage, power dynamics, and consumption patterns in a smart grid. It also offers an IoT based solution for load management and load shedding within the smart grid. The complete prototype overall demonstrates a comprehensive approach to 1) smart grid management, 2) environmental analysis, 3) security, and 4) energy monitoring. [ABSTRACT FROM AUTHOR]

The paper presents the essential theoretical elements related to the construction and operation of numerical control machines, starting from a study of the theoretical aspects related to the design of a CNC typewriter. The block diagrams of the machine, the interconnections between the component blocks and the operation of the whole system are highlighted. The paper also describes the implementation of the typewriter. It starts from a detailed diagram of the wiring and connections between the component elements, up to the presentation and commentary of how to create the program for the microcontroller used. Finally, the testing and operation of this CNC is detailed, from the design of the drawing to its actual realization, with the help of the designed and implemented assembly. CNC systems allow the repetitive production of the same parts, exactly the same and without deviations. Unlike a human operator who cannot execute two identical parts, the repeatability achieved by machines with numerical controls is clearly superior, so the reproducibility component is ensured. [ABSTRACT FROM AUTHOR]

In unstructured terrain, snakes can move more efficiently by actively pushing and avoiding obstacles, a capability believed to be realized through a decentralized mechanism. Moreover, considering harsh and unpredictable rescue environments where snake robots are expected to be deployed, such as post-earthquake scenarios, some joint sensors are prone to failure. We propose a decentralized adaptation mechanism for snake robots to navigate through random pole environments. This mechanism integrates Fault-Tolerant Joint State Feedback Adaptive Control (FT-JSFAC) with Extended Curvature Derivatives control (ECD) and Angular Damping control (AD), leveraging the FT-JSFAC method to maintain operational robustness even when some joint sensors fail. To meet critical goals of adaptability, we utilize real-time angle and electrical current data from the robot's internal servo motors. Using this data, FT-JSFAC determines whether an obstacle is beneficial or detrimental to propulsion and then allows for decentralized torque adjustment to adapt to the environment. FT-JSFAC also employs historical data from functioning joints to compensate for erroneous sensor data, ensuring operational robustness even with joint sensor failure. Simulation experiments demonstrate that the proposed mechanism effectively adapts to environmental obstacles and maintains adaptability when one or two joint sensors fail. [ABSTRACT FROM AUTHOR]

Summary: Rock drilling jumbo is an important large construction machine used for tunneling construction, and its automation has an urgent demand in engineering. However, the electro‐hydraulic system of the rock drilling jumbo has strong parameters uncertainties and some dynamics that are hard to model accurately, which causes certain challenges for designing model‐based high‐performance control algorithms. To solve these challenges, a parameter adaptive based neural network sliding mode control algorithm is proposed to enhance control performance of the electro‐hydraulic system. The parameter adaptive law is developed to estimate unknown parameters of the system, the neural network is applied for compensating unmodeled dynamics, and then the final control law is designed by sliding mode control method, and the stability demonstration of the closed‐loop system is given. In the simulations, the effectiveness of the designed parameter adaptive law is verified. Extensive comparison experiments are performed on a real rock drilling jumbo driven by proportional valves, the experimental results demonstrate that the developed control algorithm obviously improves the control precision of hydraulic cylinder of the rock drilling jumbo compared with the traditional sliding mode and PID control algorithm, thus the designed control algorithm can be expanded and applied for general hydraulic servo control mechanism. [ABSTRACT FROM AUTHOR]

With the development of artificial intelligence, reinforcement-learning-based intelligent control algorithms, which generally learn control strategies through trial and error, have received more attention in the automation equipment and manufacturing fields. Although they can intelligently adjust their control strategy without the need for human effort, the most relevant algorithms for servo motors only consider the overall performance, while ignoring the risks in special cases. Therefore, overcurrent problems are often triggered in the training process of the reinforcement learning agent. This can damage the motors' service life and even burn it out directly. To solve this problem, in this study we propose a risk-sensitive intelligent control algorithm based on value distribution, which uses the quantile function to model the probability distribution of cumulative discount returns and employs the condition value at risk to measure the loss caused by overcurrent. The agent can accordingly learn a control strategy that is more sensitive to environmental restrictions and avoid the overcurrent problem. The performance is verified on three different servo motors with six control tasks, and the experimental results show that the proposed method can achieve fewer overcurrent occurrences than others in most cases. [ABSTRACT FROM AUTHOR]

Soft material‐based robots, known for their safety and compliance, are expected to play an irreplaceable role in human‐robot collaboration. However, this expectation is far from real industrial applications due to their complex programmability and poor motion precision, brought by the super elasticity and large hysteresis of soft materials. Here, a soft collaborative robot (Soft Co‐bot) with intuitive and easy programming by contact‐based drag teaching, and also with exceptional motion repeatability (< 0.30% of body length) and ultra‐low hysteresis (< 2.0%) is reported. Such an unprecedented capability is achieved by a biomimetic antagonistic design within a pneumatic soft robot, in which cables are threaded to servo motors through tension sensors to form a self‐sensing system, thus providing both precise actuation and dragging‐aware collaboration. Hence, the Soft Co‐bots can be first taught by human drag and then precisely repeat various tasks on their own, such as electronics assembling, machine tool installation, etc. The proposed Soft Co‐bots exhibit a high potential for safe and intuitive human‐robot collaboration in unstructured environments, promoting the immediate practical application of soft robots. [ABSTRACT FROM AUTHOR]

In a clinical context, conventional optical microscopy is commonly used for the visualization of biological samples for diagnosis. However, the availability of molecular techniques and rapid diagnostic tests are reducing the use of conventional microscopy, and consequently the number of experienced professionals starts to decrease. Moreover, the continuous visualization during long periods of time through an optical microscope could affect the final diagnosis results due to induced human errors and fatigue. Therefore, microscopy automation is a challenge to be achieved and address this problem. The aim of the study is to develop a low-cost automated system for the visualization of microbiological/parasitological samples by using a conventional optical microscope, and specially designed for its implementation in resource-poor settings laboratories. A 3D-prototype to automate the majority of conventional optical microscopes was designed. Pieces were built with 3D-printing technology and polylactic acid biodegradable material with Tinkercad/Ultimaker Cura 5.1 slicing softwares. The system's components were divided into three subgroups: microscope stage pieces, storage/autofocus-pieces, and smartphone pieces. The prototype is based on servo motors, controlled by Arduino open-source electronic platform, to emulate the X-Y and auto-focus (Z) movements of the microscope. An average time of 27.00 ± 2.58 seconds is required to auto-focus a single FoV. Auto-focus evaluation demonstrates a mean average maximum Laplacian value of 11.83 with tested images. The whole automation process is controlled by a smartphone device, which is responsible for acquiring images for further diagnosis via convolutional neural networks. The prototype is specially designed for resource-poor settings, where microscopy diagnosis is still a routine process. The coalescence between convolutional neural network predictive models and the automation of the movements of a conventional optical microscope confer the system a wide range of image-based diagnosis applications. The accessibility of the system could help improve diagnostics and provide new tools to laboratories worldwide. [ABSTRACT FROM AUTHOR]

This paper focuses on the study of the tracking performance of a novel two-degrees-of-freedom (two-DOF) voice coil motor (VCM). Intelligent control algorithms estimate the motor control model by the relationship between the input and output values, and it is hard to achieve excellent tracking performance due to the wider variational range of motor electromagnetic parameters (MEPs). This paper proposes estimated methods for MEPs and an adaptive feedforward control algorithm based on estimated MEPs (ACBE). ACBE can alter its control parameters from inside out in time with the change in MEPs. Experiments are carried out to verify that the proposed ACBE realized excellent tracking performance upon the novel two-DOF VCM. This study indicates that an adaptive control algorithm with high-precision control parameters has better tracking performance upon a motor control model with large variation. [ABSTRACT FROM AUTHOR]

At present, HTS magnets cannot operate in the real closed-loop persistent current mode due to the existence of joint resistance, flux creep, and AC loss of the HTS tape. Instead of using a current source, HTS flux pumps are capable of injecting flux into closed HTS magnets without electrical contact. This paper presents a practical superconducting DC dynamo for charging a conduction-cooled HTS magnet system based on a flux-pumping technique. To minimize heat losses, the rotor is driven by a servo motor mounted outside the vacuum dewar by utilizing magnetic fluid dynamic sealing. Different parameters, such as air gap and rotating speed, have been tested to investigate the best pumping effect, and finally, it successfully powers a 27.3 mH HTS non-insulated double-pancake coil to the current of 54.2 A within 76 min. As a low-cost and compact substitute for the traditional current source, the realization of a contactless DC power supply can significantly improve the flexibility and mobility of the HTS magnet system and could be of great significance for the technological innovation of future HTS magnets used in offshore wind turbines, biomedical, aerospace, etc. [ABSTRACT FROM AUTHOR]

This paper presents a biomimetic fish robot featuring a flexible spine driven by cables, which integrates the cable-driven mechanism with a flexible spine. The drive system separates the body and tail fin drives for control, offering enhanced flexibility and ease in achieving phase difference control between the body and tail fin movements compared to the conventional servo motor cascaded structure. A prototype of the biomimetic fish robot was developed, accompanied by the establishment of a kinematic model. Based on this model, a control method for the biomimetic fish is proposed. Additionally, we introduce the concept of prestress to establish a numerical model for the biomimetic fish. Using multi-physical field simulation software, we simulate the two-dimensional autonomous swimming process of the biomimetic fish under different flapping frequencies and solve for its swimming characteristics as well as hydrodynamic properties. Both the simulation and experimental results validate the accuracy of our kinematic model. [ABSTRACT FROM AUTHOR]

Lost motion is utilized to characterize the transmission accuracy of gear reducers and is commonly evaluated through the hysteresis curve method. In examinations of lost motion for large and medium-sized reducers, the default practice is the application of the equal torque gradient loading method. Nonetheless, for small-sized reducers, this approach is deemed inappropriate due to the constraints of the servo motor loading resolution. This study reveals that employing a larger unit torque for equal torque gradient loading can modify the shape of the hysteresis curve and influence the assessment of lost motion. As a result, this paper introduces two innovative loading techniques, namely equal position gradient loading and uniform speed loading, to address the limitations of equal torque gradient loading and reduce the demands on testing equipment. Subsequent experiments validate the issues associated with equal torque gradient loading, confirm the effectiveness of the two new loading techniques, and yield more comprehensive hysteresis curves. It is important to note that all three loading methods are influenced by the loading rate, but the two novel methods can mitigate the effects of loading rate dependency. [ABSTRACT FROM AUTHOR]

The background of research try to use an open loop system, without feedback, by building torque in the target position. Theoretical basis manages the turning round of servo motor change direct currents to alternating currents by adjusting the rate input used. Methodology in simple terms, the flowchart of code processing from igniting transistors to managing the turning round of a three-phase alternating current (AC) servo motor. The result of the transistor ignition time with room phasor pulse width modulation (PWM) to set the ignition of a three-phase AC servo motor in the process of igniting as ordered, for manage position only igniting transistors in target position, and building torque at there. Discussion, igniting transistors to manage the turning round of servo motors, allows motion of servo motor, allows motion of servo motor to be added faster, accurately, soft, and steady. In conclusion, in this case the researcher uses it more specifically by turning on the transistor only at the target position, so that the torque generated is only at the target position, the servo motor motion from the start position immediately ends at the target position. Suggestions, this system igniting can be applied at a motion high-velocity system like a missile system controlled. [ABSTRACT FROM AUTHOR]

Copyright of Mugla Journal of Science & Technology is the property of Mugla Journal of Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Because of the difficulty in fault detection for and diagnosing the adjustment hydraulic servomotor, this paper uses feature extraction technology to extract the time domain and frequency domain features of the pressure signal of the adjustment hydraulic servomotor and splice the features of multiple pressure signals through the Multi-source Information Fusion (MSIF) method. The comprehensive expression of device status information is obtained. After that, this paper proposes a fault detection Algorithm GA-SVDD-neg, which uses Genetic Algorithm (GA) to optimize Support Vector Data Description with negative examples (SVDD-neg). Through joint optimization with the Mutual Information (MI) feature selection algorithm, the features that are most sensitive to the state deterioration of the adjustment hydraulic servomotor are selected. Experiments show that the MI algorithm has a better performance than other feature dimensionality reduction algorithms in the field of the abnormal detection of adjustment hydraulic servomotors, and the GA-SVDD-neg algorithm has a stronger robustness and generality than other anomaly detection algorithms. In addition, to make full use of the advantages of deep learning in automatic feature extraction and classification, this paper realizes the fault diagnosis of the adjustment hydraulic servomotor based on 1D Convolutional Neural Network (1DCNN). The experimental results show that this algorithm has the same superior performance as the traditional algorithm in feature extraction and can accurately diagnose the known faults of the adjustment hydraulic servomotor. This research is of great significance for the intelligent transformation of adjustment hydraulic servomotors and can also provide a reference for the fault warning and diagnosis of the Electro-Hydraulic (EH) system of the same type of steam turbine. [ABSTRACT FROM AUTHOR]

To address the inefficiency and instability of automatic transplanting machines, a dual-row seedling pick-up device and its corresponding control system were developed. Existing seedling end-effectors are primarily mechanically controlled, and the seedling needles can easily cause damage to the interior of the bowl. In order to reduce the damage inflicted by the end-effectors to the bowl, this paper conducted a mechanical analysis of the end-effector. At the same time, a buffer optimization analysis was conducted on the operation of the end-effector, and a flexible pneumatic end-effector for seedling picking was designed. The control system combined the detection of multiple sensors to monitor the process of seedling picking and throwing. By coordinating the lifting cylinder and clamping cylinder, the system effectively reduced seedling pot damage while improving seedling picking efficiency. By setting the operating parameters of the servo motor, the goal of low-speed and high-efficiency seedling picking was achieved. To evaluate the performance of the control system, the linear displacement sensors and acceleration testing systems were used to analyze the performance of the seedling throwing. The results showed that the seedling picking efficiency could reach 180 plants min−1, with no significant difference between the actual measured moving distance and the theoretical setting distance. The positioning error remained stable between 0.5 and 0.9 mm, which met the requirements for seedling picking accuracy. The buffer optimization design reduced the peak acceleration of the end-effector from −22.1 m/s2 to −13.4 m/s2, and the peak value was reduced by 39.4%, which proved the significant effectiveness of the buffer design. A performance test was conducted using 128-hole seed trays and 33-day-old cabbage seedlings for seedling picking and throwing. When the planting frequency reached 90 plants/row·min−1, the average success rate of picking and throwing seedlings was 97.3%. This indicates that the various components of the designed seedling pick-up device work in good coordination during operation, and the control system operates stably. Technical requirements for the automatic mechanical transplanting of tray seedlings were achieved, which can provide reference for research on automatic transplanting machines. [ABSTRACT FROM AUTHOR]

A new design for humanoid arms is presented based on a tripod mechanism that is actuated by linear servomotors. A specific prototype is built and tested, with the results of performance characterization verifying a possible implementation on the LARMbot humanoid. The design solves the main requirements in terms of a high payload ratio with respect to arm weight by using a tripod architecture with parallel manipulator behavior. The built prototype is assembled with commercial components to match the expectations for low-cost user-oriented features. The test results show satisfactory operation characteristics both in motion and force performance, which will ensure a future successful implementation in the LARMbot humanoid structure. [ABSTRACT FROM AUTHOR]

Many applications require variable speed operation. The motor speed needs to be controlled to save more power. It became highly imperative for further research to find out an efficient method that can yield an optimal speed control. This study presents the design and modeling of a proportional derivative controller for a three-phase induction motor speed control. The scalar control methodology was used to investigate the performance of motor speed control. For the controller approach, proportional-integral (PI) and proportional-derivative (PD) controllers were investigated. Simulation results using MATLAB (Simulink) software is presented. Furthermore, investigation of the PI, and PD performance shows that the PI controller performed poorly due to existence of high peaks, overshoots and rise time. However, the PD controller yielded satisfactory results. Hence, PD controller revealed a better performance with a 1.01s settling time and a steady state error of 1.0 as against that of the PI controller which was unstable, an overshoot of approximately 96% and a steady state error of 1.22. [ABSTRACT FROM AUTHOR]

A dual‐motor servo mechanism is a high‐order and strong‐coupling system with unknown nonlinearity, which brings challenges to controller design to realize high‐performance tracking and synchronization. This article proposes a finite‐time command filtered control strategy to address this problem. In tracking control design, finite‐time command filters are adopted to obtain the derivatives of virtual controllers, and the "explosion of complexity" problem in backstepping is thus solved. An improved compensation system is designed to reduce filtering errors. The tracking control is developed based on the combination of finite‐time control and command filtered approach. Moreover, to deal with unknown nonlinearities and uncertainties, fast finite‐time extended state observers are developed to observe lumped disturbances for the load and motor, respectively. In synchronization control design, two opposite control actions are developed using the speed difference to force two motors to rotate synchronously. The finite‐time convergence of the tracking and synchronization errors is proved. The efficiency of the proposed control strategy is verified via experiments conducted on a dual‐motor servo turntable. [ABSTRACT FROM AUTHOR]

Although the cardioid-shaped traffic loading path can be implemented using hollow cylinder apparatus, the preparation of inherently anisotropic sand with different bedding plane angles could be difficult. Consequently, the macro-scale response of inherently anisotropic sand under traffic loading has not been adequately investigated to reveal the underlying microscopic mechanism. In this paper, elongated particles with various aspect ratios were used to approximate the natural sand particles, and uniform three-dimensional specimens with different bedding plane angles were generated using discrete element method based on a modified version of under-compaction method. The cardioid-shaped loading path was implemented using an advanced servomechanism that can apply arbitrary loading paths. The internal structure of specimen was quantified through a contact-normal-based fabric tensor, which could describe the load-bearing structure of granular specimens. The interplay between the macro-scale observations and the fabric evolutions was elucidated. The influences of both bedding plane angle and aspect ratio on the accumulations of volumetric strain and generalized shear strain are not monotonic, with the largest strains at the bedding plane angle of 45° and the aspect ratio of 1.4. Results provide useful insights into the underlying mechanism of the deformation behavior of inherently anisotropic granular materials under traffic loading. [ABSTRACT FROM AUTHOR]

The undulator is a key luminous component of the Shanghai high repetition rate x-ray free electron laser and extreme light facility, and the motion control system is an important part of the undulator. The main task of the motion control system is to complete the high precision adjustment of the gap and taper between the upper magnetic pole girder and lower magnetic pole girder, so as to adjust the wavelength of the radiation light. According to the development requirements of the motion control system for the U26 undulator, which is a conventional permanent magnet, this paper proposes a new motion control system with double position feedback closed-loop control, including programmable logic controller (PLC) closed-loop control based on position feedback by a linear absolute encoder (LAE) and driver closed-loop control based on position feedback by a rotary absolute encoder (RAE) of a servo motor. Multiple motion tests of the U26 undulator have shown that the repeatability accuracy of the gap is ±50 nm and the gap drive can reach 0.1 µm step size, the error of which is about ±20 nm according to the feedback of the LAE. The conclusion can be drawn that the motion step size and repeatability accuracy of the motion control system for the U26 undulator are improved by one order of magnitude on the basis of meeting all technical requirements. At the same time, motor torque protection, motor temperature protection, and redundant position protection with RAE can further improve the reliability and safety of the motion control system for the U26 undulator. [ABSTRACT FROM AUTHOR]

The electro-hydraulic servo system has advantages such as high pressure, large flow, and high power, etc., which can also realize stepless regulation, so it is widely used in many engineering machineries. A linear model is sometimes only a simple approximation of an idealized model, but in an actual system, there may be nonlinear and transient variation characteristics in the systems. Coupling is reflected in the fact that the components or functional structures implemented by each system used for the design of hydraulic systems are not completely or independently related to each other, but affect each other. The nonlinear clearance between the actuator and the load reduces the control accuracy of the system and increases the impact, thus losing stable working conditions. In the paper, based on the nonlinear clearance problem of the electro-hydraulic servo system, a mathematical transfer model with clearance is established, and on this basis, a clearance compensation method based on the Hopfield neural network is proposed. In this way, clearance compensation can be realized by adjusting the parameters of neural network nodes, through simple and convenient operation. Finally, by setting different clearance values, the results of the step response and sine response curve before and after clearance compensation of the hydraulic system are compared, and the effectiveness of Hopfield neural network compensation clearance control is verified based on the comparison simulation results. [ABSTRACT FROM AUTHOR]

Water quality is crucial to the health of the prawn industry in Malaysia, where unpredictable weather is common. However, many breeders still monitor the water quality manually, which limits their capacity to respond quickly to changing conditions. To address this, an automated system was developed using Internet of Things (IoT) technology to continually monitor and control the pH level and temperature of the saltwater. Sensors are connected to a LabVIEW-equipped data acquisition, and a servo motor operates the probe of the sensors. The proposed system employs ThingSpeak software to display real-time water quality data and has a system of alarms that can be activated to notify the user of any issues. An acid or alkali solution is pumped into the tank using a submersible water pump to regulate the pH level, and a fuzzy logic controller is integrated into the submersible water pump to control the valve for the solutions. From the results, the systems managed to measure the maximum value of the temperature which is 33.86°C meanwhile the minimum value is 30.6 °C. These temperature values are in the desirable range of temperature for prawn which is between 25 °C to 35 °C. Hence, this system depicts that the water is a good temperature for the prawn. Furthermore, the data transfer through wireless via ThingSpeaks' website is the same as the data transfer through mobile's app. Hence, this prove that the system is able to deliver the water quality data accurately and can be monitored remotely. The system will greatly benefit the aquaculture industry, and continued development will only improve its effectiveness. [ABSTRACT FROM AUTHOR]

In order to improve the obstacle avoidance control performance and anti-interference ability of a stubble breaking device of a no-tillage planter, a back-propagation neural network (BPNN)-optimized fuzzy active disturbance rejection control (ADRC) controller was designed to optimize the control performance of a servo motor. Firstly, a negative feedback mathematical model was established for the obstacle avoidance control system. Then, the nonlinear state error feedback (NLSEF) parameters in the fuzzy ADRC were intelligently optimized by the BPNN algorithm. In this way, a fuzzy ADRC controller based on BPNN optimization was formed to optimize the control process of a servo motor. Matlab/Simulink (R2022b) was used to complete the simulation model design and parameter adjustment. Consequently, the response time was 0.089 s using the BPNN fuzzy ADRC controller, which was shorter than the 0.303 s of the ADRC controller and the 0.100 s of the fuzzy ADRC controller. The overshoot was 0.1% using a BPNN fuzzy ADRC controller, which was less than the 2% of the ADRC controller and the 1% of the fuzzy ADRC controller. After noise signal interference was introduced into the control system, the regression steady state time of the BPNN fuzzy ADRC controller was 0.22 s, which was shorter than the 0.56 s of the ADRC controller and the 0.45 s of the fuzzy ADRC controller. A hardware-in-the-loop simulation experimental platform of the obstacle avoidance control system was constructed. The experiment results show that the servo motor control system has a fast dynamic response, small steady-state error and strong anti-interference ability for obstacle avoidance at the target height. Then, the control system error was within the allowable range. The servo motor control effect of the BPNN fuzzy ADRC was better than the ADRC and fuzzy ADRC. This optimized servo motor control method can provide a reference for improving the obstacle avoidance control effect problem of no-tillage seeders in stubble breaking operations on rocky desertification areas. [ABSTRACT FROM AUTHOR]