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Due to the inherent temperature drift and lack of static stability in traditional pressure sensors, which make it difficult for them to meet the increasing demands of various industries, this paper designs a new system. The proposed system integrates temperature measurement and regulation circuits, signal processing, and communication circuits to accurately acquire and transmit pressure sensor data. The system designs a filtering algorithm to filter the original data and develops a data-fitting operation to achieve error compensation of the static characteristics. In order to eliminate the temperature drift problem of the sensor system, the system also adopts an improved PID thermostatic control algorithm to compensate for the temperature drift. Finally, it can also transmit the processed pressure data remotely. The experimental results show that the nonlinear error at 50 °C is reduced from the initial 1.82% to 0.24%; the hysteresis error is significantly reduced from 1.23% to 0.046%; and the repeatability error control is reduced from 3.79% to 0.89%. By compensating for thermal drift, the system's thermal sensitivity drift coefficient is reduced by 74.67%, the thermal zero drift coefficient is reduced by 66.24%, and the wireless communication range is up to 1km. The above significant optimization results fully validate the high accuracy and stability of the system, which is perfectly suited for demanding pressure measurement applications. [ABSTRACT FROM AUTHOR]

The traditional automobile suspension system has certain limitations when dealing with different road conditions and driving conditions and cannot be flexibly adjusted to provide the best suspension performance and ride comfort. Therefore, this study uses adaptive differential evolution algorithm dynamic control system for automotive air suspension to improve the performance of the vehicle's suspension. The system adopts adaptive differential evolution algorithm as the core control strategy to dynamically adjust the parameters and control strategy of the suspension system to adapt to different road conditions and driving conditions. The root-mean-square value of the vertical acceleration at the center of mass of the vehicle is reduced by 15.2% under the medium speed condition. The root-mean-square value of four-wheel suspension dynamic deflection is reduced by 8.46%. The root-mean-square value of the dynamic load of the four-wheel tire is only slightly increased by 0.47%. The root-mean-square value of the total weighted acceleration of the driver and the rear seat of the same side of the experimental vehicle after modification is in the range of 0.315-0.63. The application of adaptive differential evolution algorithm dynamic control system technology for automotive air suspension has promoted the development of automotive technology and provided a new control idea and method for automobile manufacturers and research institutions. [ABSTRACT FROM AUTHOR]

Introduction: Long-term imaging of live cells is commonly used for the study of dynamic cell behaviors. It is crucial to keep the cell viability during the investigation of physiological and biological processes by live cell imaging. Conventional incubators that providing stable temperature, carbon dioxide (CO2) concentration, and humidity are often incompatible with most imaging tools. Available commercial or custom-made stage-top incubators are bulky or unable to provide constant environmental conditions during long time culture.Methods: In this study, we reported the development of the microscope incubation system (MIS) that can be easily adapted to any inverted microscope stage. Incremental PID control algorithm was introduced to keep stable temperature and gas concentration of the system. Moreover, efficient translucent materials were applied for the top and bottom of the incubator which make it possible for images taken during culture.Results: The MIS could support cell viability comparable to standard incubators. When used in real time imaging, the MIS was able to trace single cell migration in scratch assay, T cell mediated tumor cells killing in co-culture assay, inflation-collapse and fusion of organoids in 3D culture. And the viability and drug responses of cells cultured in the MIS were able to be calculated by a label-free methods based on long term imaging.Discussion: We offer new insights into monitoring cell behaviors during long term culture by using the stage adapted MIS. This study illustrates that the newly developed MIS is a viable solution for long-term imaging during in vitro cell culture and demonstrates its potential in cell biology, cancer biology and drug discovery research where long-term real-time recording is required.

Due to the inherent temperature drift and lack of static stability in traditional pressure sensors, which make it difficult for them to meet the increasing demands of various industries, this paper designs a new system. The proposed system integrates temperature measurement and regulation circuits, signal processing, and communication circuits to accurately acquire and transmit pressure sensor data. The system designs a filtering algorithm to filter the original data and develops a data-fitting operation to achieve error compensation of the static characteristics. In order to eliminate the temperature drift problem of the sensor system, the system also adopts an improved PID thermostatic control algorithm to compensate for the temperature drift. Finally, it can also transmit the processed pressure data remotely. The experimental results show that the nonlinear error at 50 °C is reduced from the initial 1.82% to 0.24%; the hysteresis error is significantly reduced from 1.23% to 0.046%; and the repeatability error control is reduced from 3.79% to 0.89%. By compensating for thermal drift, the system’s thermal sensitivity drift coefficient is reduced by 74.67%, the thermal zero drift coefficient is reduced by 66.24%, and the wireless communication range is up to 1km. The above significant optimization results fully validate the high accuracy and stability of the system, which is perfectly suited for demanding pressure measurement applications.

The traditional PID algorithm used in the currently existing automatic train operation system is limited due to fixed parameters, making it difficult to achieve excellent control effects in actual operation scenes featuring strong coupling and high nonlinearity, which is mainly attributed to difficulties in overcoming nonlinear disturbances.In light of this, this paper proposes an automatic train operation approach that relies on a fuzzy adaptive PID algorithm, which can adjust the PID parameters in real time according to the preset fuzzy rules, thus improving the PID controller's performance in speed tracking and leading to an improved train control effect. Based on the data from Changsha Rail Transit Line 4, the semi-physical simulation results show that the proposed algorithm resulted in the average root-mean-square error (RMSE) of 18.876 cm/s between the actual train speed and the recommended speed, which is less than the 35.200 cm/s of the traditional PID controller and the value of fitting degree is 1.69 m/s between travel speed and the recommended speed, which is less than the 2.25 m/s of the traditional PID controller, suggesting that the proposed algorithm offers a more effective solution for tracking the recommended speed curves and improving system operation efficiency.

The usage of Autonomous mining vehicles at mining sites leads to remarkable improvement in the mining industry with efficient truck hauling, safety, and driving assistance. The steering mechanism is one major component of mining shuttle anatomy design. A significant share of failure in safety measures of the mining shuttle is due to steering imbalance. Steering stability is one of the key components of any mining truck design specifically in the recent emerging technology of intelligent transportation systems such as autonomous truck haul. The earlier steering mechanisms for the heavy truck such as the Davis steering mechanism and other steering mechanisms available in both sliding and turning pairs will be present in the front wheel axle which has less stability of tires in a curved path. To overcome the problem, this paper proposes the design of an enhanced Ackermann steering system to meet the stability, control, and other steering capability of mining trucks by turning the front wheels at different angles. This paper also discusses the methodology to implement the designed principles using 1/10th scale of an original vehicle prototype built using STM 32 microcontroller by 3D printing, whose movement is controlled with Remote Control (RC). Hence the designed prototype model prototype with its innovative gear system provides mobility to the mining shuttle without loss in energy due to friction leading to fuel efficient, safe, stable intelligent transport system with green technology. [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.)

Aimed at the problem of severed heads caused by the large fluctuation of yarn tension in the winding process of the spinning machine, the spindle speed control method of GPC-PID optimized by particle swarm optimization(PSO) algorithm was proposed. First, the generalized predictive control PID (GPC-PID) algorithm was introduced to control the spindle speed, and the PID parameters were adjusted in real time to control the spinning speed. Then, PSO algorithm was introduced to improve the prediction accuracy of GPC-PID. Finally, through simulation experiments, the conventional GPC-PID control was compared with the GPC-PID control optimized by PSO algorithm. The results show that under the control of GPC-PID algorithm optimized by PSO algorithm, the speediness and stability of the system are improved, the spindle speed and torque are effectively controlled, the yarn tension fluctuation is small, and the breakage rate in the spinning process is reduced, which proves the superiority of particle swarm optimization GPC-PID control algorithm.

In emergency situations, it is difficult to meet the requirements of safe driving only by relying on the braking system, and the probability of accidents can be reduced by employing an emergency lane-changing mode. To improve the adaptability of the distributed electric vehicle adaptive cruise control (ACC) strategy to complicated and volatile conditions, a multimode ACC strategy with emergency lane-changing function is proposed. Firstly, the ACC is divided into four modes aimed at the problem of complex conditions, and a switching strategy is designed to control the switching of them. Simultaneously, the car-following mode is divided in greater detail based on time to collision (TTC), and the acceleration weighted average algorithm is adopted for accuracy and output continuity during switching. Then, the ACC is established with a hierarchical control framework, in which a PID-based cruise mode and a multi-objective optimized car-following mode based on model predictive control (MPC) are devised. The target brake wheel cylinder pressure is selected as the emergency brake pressure in takeover mode. In addition to the MPC-based system, the emergency lane-changing mode incorporates a yaw moment controller in the upper-level controller to improve body stability during emergency lane changing in the upper-level controller. In the lower-level controller, the upper-level output is converted into driving torque, wheel cylinder pressure, and front wheel angle to control vehicle travel and generate additional yaw moment. Finally, the results indicate that the presented multimode switching strategy can adapt to complex and instable transportation environments. In the cruise control scenario, the host vehicle can rapidly reach cruising speed within 5 s. In the car-following scenario, the host vehicle can stably follow the preceding vehicle with an acceleration of −5–3.5 m/s2 and a jerk of −2–2 m/s3 throughout the entire process, maintaining a safe distance from the preceding vehicle. In emergency lane-changing scenarios, vehicles with body stability control can better follow the lane-changing trajectory, and tracking accuracy is improved by 65%. Simultaneously, parameters such as front wheel angle, yaw rate, sideslip rate, and lateral acceleration remain within the normal range. In mixed switching scenarios, each mode can be correctly switched according to diverse operating conditions, and obstacle avoidance can be accomplished through horizontal and vertical strategies, which also verify the effectiveness and rationality of the control strategy proposed. [ABSTRACT FROM AUTHOR]

In order to improve the communication quality of visible light downlink, an automatic alignment system for visible light communication based on OpenMV is designed in this study. The system realizes automatic recognition of indoor white LED is based on image processing and color recognition. The system uses gray-scale centroid method to determine the centroid coordinates of white LED, and the PID algorithm is used to drive steering gears to achieve the tracking of the indoor white light LED. The experimental results show that the automatic alignment system of visible light communication can realize the automatic alignment of white LED under various motion trajectories at the receiving distance of 2 m, and the maximum alignment angle error is less than 0.534°. In addition, whether the white LED is blocked or there is an interfering light source, system can still maintain the good tracking effect, indicating that system has good robustness. [ABSTRACT FROM AUTHOR]

Aimed at the problem of severed heads caused by the large fluctuation of yarn tension in the winding process of the spinning machine, the spindle speed control method of GPC-PID optimized by particle swarm optimization（PSO） algorithm was proposed. First, the generalized predictive control PID（GPC-PID） algorithm was introduced to control the spindle speed, and the PID parameters were adjusted in real time to control the spinning speed. Then, PSO algorithm was introduced to improve the prediction accuracy of GPC-PID. Finally, through simulation experiments, the conventional GPC-PID control was compared with the GPC-PID control optimized by PSO algorithm. The results show that under the control of GPC-PID algorithm optimized by PSO algorithm, the speediness and stability of the system are improved, the spindle speed and torque are effectively controlled, the yarn tension fluctuation is small, and the breakage rate in the spinning process is reduced, which proves the superiority of particle swarm optimization GPC-PID control algorithm. [ABSTRACT FROM AUTHOR]

Copyright of Computer Measurement & Control is the property of Magazine Agency of Computer Measurement & Control 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.)

DC to DC converters are apparatuses that can save electrical power for transforming DC to specific voltage. It can act as necessitate element among systems that operate at distinct voltage levels across the car and other automotive vehicles. By gradually raising the engine’s Hp output, the controller’s known as PID can give back the measured speed to the required speed. A PID controller is added to the converter, which enhances dynamic response and lowers steady-state error. The integrated controller (KI) will reduce the steady-state error, while a derivative controller (KD) will improve the transient responsiveness. However, in large-signal domains with a boost converter, the convex PID doesn’t work as desired. For this, PID-NN can be proposed. The “PID-NN controller” is capable of effectively enhancing the rejection of possible voltage input fluctuations. Additionally, the “PID-NN controller” has been found to be more effective in controlling the output voltage. Hence, the current work has been proposed on the same for high power application of DC to DC converter based on PID-NN.

In this paper - we present our research and experimentation with the Arduino mobile robot. We have developed a control algorithm for robot movement along a given trajectory. The basic methods of operation ofthe Arduino platform, its restrictions, and its main functionalities are explained in the paper. In our work - we have applied the available Arduino software tools and functions. We have developed custom software code for robot movement control, by utilizing the existing software for the motor board of the Arduino robot. We have investigated different algorithms for line (trajectory) following - P, PI, PID. The PID algorithm (proportional-integral-differential) hasproved to be the most efficient algorithm that allows the robot to smoothly follow the line at high speeds without any short-term departures from it. The paper shows how to implement the algorithm, and at the same time how to quickly and finely adjust the parameters of the PID algorithm. We emphasized the importance of having a stable platform for algorithm implementation(line tracking), and for a proper response of the microcontroller's board components. [ABSTRACT FROM AUTHOR]

Temperature control is a critical aspect for the semiconductor material growth of the Molecular Beam Epitaxy system. The growth rate depends on the temperature of the beam source, and the quality of epi-layers heavily depends on the temperature of the substrate. In this paper, we reported an intelligent temperature control algorithm based on the BP neural network, which is specially optimized for the Molecular Beam Epitaxy system. After training the BP neural network by the collected temperature data of the Molecular Beam Epitaxy, the intelligent temperature control algorithm keeps the temperature error within 0.1°C. Moreover, this intelligent algorithm in the field of Molecular Beam Epitaxy achieves a better control effect, reduces the regulation time of the system and makes the system overshoot to zero.

A synchronous motion-based control strategy for unmanned aerial vehicle (UAV) landing on an unmanned surface vehicle (USV) is proposed to address the problem of low accuracy or even failure of UAV landing on the surface of a USV under wave action. Firstly, the landing marks are identified and localized based on computer vision; secondly, the USV attitude angle is predicted based on a bidirectional long-short term memory (Bi-LSTM) neural network to ensure that the UAV can respond to USV attitude changes in real-time; furthermore, the UAV attitude controller is designed based on a PID algorithm to realize UAV–USV synchronous motion. The experimental results demonstrate that the proposed UAV–USV synchronous motion landing scheme with high landing accuracy is more suitable for the UAV to achieve autonomous landing on a USV in a complex marine environment. [ABSTRACT FROM AUTHOR]

In emergency situations, it is difficult to meet the requirements of safe driving only by relying on the braking system, and the probability of accidents can be reduced by employing an emergency lane-changing mode. To improve the adaptability of the distributed electric vehicle adaptive cruise control (ACC) strategy to complicated and volatile conditions, a multimode ACC strategy with emergency lane-changing function is proposed. Firstly, the ACC is divided into four modes aimed at the problem of complex conditions, and a switching strategy is designed to control the switching of them. Simultaneously, the car-following mode is divided in greater detail based on time to collision (TTC), and the acceleration weighted average algorithm is adopted for accuracy and output continuity during switching. Then, the ACC is established with a hierarchical control framework, in which a PID-based cruise mode and a multi-objective optimized car-following mode based on model predictive control (MPC) are devised. The target brake wheel cylinder pressure is selected as the emergency brake pressure in takeover mode. In addition to the MPC-based system, the emergency lane-changing mode incorporates a yaw moment controller in the upper-level controller to improve body stability during emergency lane changing in the upper-level controller. In the lower-level controller, the upper-level output is converted into driving torque, wheel cylinder pressure, and front wheel angle to control vehicle travel and generate additional yaw moment. Finally, the results indicate that the presented multimode switching strategy can adapt to complex and instable transportation environments. In the cruise control scenario, the host vehicle can rapidly reach cruising speed within 5 s. In the car-following scenario, the host vehicle can stably follow the preceding vehicle with an acceleration of −5–3.5 m/s2 and a jerk of −2–2 m/s3 throughout the entire process, maintaining a safe distance from the preceding vehicle. In emergency lane-changing scenarios, vehicles with body stability control can better follow the lane-changing trajectory, and tracking accuracy is improved by 65%. Simultaneously, parameters such as front wheel angle, yaw rate, sideslip rate, and lateral acceleration remain within the normal range. In mixed switching scenarios, each mode can be correctly switched according to diverse operating conditions, and obstacle avoidance can be accomplished through horizontal and vertical strategies, which also verify the effectiveness and rationality of the control strategy proposed.

Introduction: Long-term imaging of live cells is commonly used for the study of dynamic cell behaviors. It is crucial to keep the cell viability during the investigation of physiological and biological processes by live cell imaging. Conventional incubators that providing stable temperature, carbon dioxide (CO 2 ) concentration, and humidity are often incompatible with most imaging tools. Available commercial or custom-made stage-top incubators are bulky or unable to provide constant environmental conditions during long time culture. Methods: In this study, we reported the development of the microscope incubation system (MIS) that can be easily adapted to any inverted microscope stage. Incremental PID control algorithm was introduced to keep stable temperature and gas concentration of the system. Moreover, efficient translucent materials were applied for the top and bottom of the incubator which make it possible for images taken during culture. Results: The MIS could support cell viability comparable to standard incubators. When used in real time imaging, the MIS was able to trace single cell migration in scratch assay, T cell mediated tumor cells killing in co-culture assay, inflation-collapse and fusion of organoids in 3D culture. And the viability and drug responses of cells cultured in the MIS were able to be calculated by a label-free methods based on long term imaging. Discussion: We offer new insights into monitoring cell behaviors during long term culture by using the stage adapted MIS. This study illustrates that the newly developed MIS is a viable solution for long-term imaging during in vitro cell culture and demonstrates its potential in cell biology, cancer biology and drug discovery research where long-term real-time recording is required., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Yan, Wu, Li, Feng, Ge, Zhang and Dong.)

Copyright of Oil Drilling & Production Technology / Shiyou Zuancai Gongyi is the property of Shiyou Zuancai Gongyi Bianjibu 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.)

Abstract Poor user experience is caused by the current unstable operation of the two-wheel self-balancing vehicle control system, the high failure rate, and the poor accuracy and sensitivity of the control system (prone to deviation). Therefore, the work studied the two-wheel self-balancing vehicle system with the visual recognition of vehicle attitude. Kalman filtering and PID control algorithm were adopted to reduce the high frequency interference of the accelerometer and the low frequency error of the gyroscope, improve the response speed and control precision of motor to error, and ensure vertical control. The road images were acquired by a charge-coupled device vision sensor with the edge information extracted by the Laplacian operator, which ensures autonomous navigation control of a balance car. Based on the calculation of the distance between road axis and the existence detection of forward obstacles, the early warning mechanism was established through the calculation of the group agent to improve the safety performance of a balance vehicle. Experiments showed the improved control system has good stability, fast walking speed, strong anti-interference, and high security.

The self-sensing technique allows a single piece of piezoelectric element to function simultaneously as an actuator and a sensor in a closed-loop system. This study proposes an improved vibration suppression system using the piezoelectric self-sensing technique whose usefulness is experimentally verified in a cantilever beam. A single piezoelectric element is bonded to the root of the beam and functions as an actuator and a sensor simultaneously. A mirror circuit constructed with two charge driver circuits is used to pick up the sensing signal from the driving voltage signal. Then, a closed-loop control strategy based on the proportion integration differentiation (PID) algorithm can adjust the sensing signal precisely to suppress the vibration of the cantilever beam quickly. The first mode of vibration is suppressed, and the amplitude of the vibration is actively dampened by a factor exceeding 96.4%. Moreover, the frequency sweep experiments demonstrate that with the PID feedback control circuit connected to the piezoelectric cantilever beam, the Q value of the system is greatly reduced, and the loss factor is increased from 0.053 to 0.288. The improved mirror circuit with PID control has a good suppression effect in the frequency range near the first order mode of the cantilever beam.

A synchronous motion-based control strategy for unmanned aerial vehicle (UAV) landing on an unmanned surface vehicle (USV) is proposed to address the problem of low accuracy or even failure of UAV landing on the surface of a USV under wave action. Firstly, the landing marks are identified and localized based on computer vision; secondly, the USV attitude angle is predicted based on a bidirectional long-short term memory (Bi-LSTM) neural network to ensure that the UAV can respond to USV attitude changes in real-time; furthermore, the UAV attitude controller is designed based on a PID algorithm to realize UAV–USV synchronous motion. The experimental results demonstrate that the proposed UAV–USV synchronous motion landing scheme with high landing accuracy is more suitable for the UAV to achieve autonomous landing on a USV in a complex marine environment.

The article considers three implementation versions of controllers operating with constant speed actuators that are used in automation systems of a technological process: with a relay-pulse control unit (RPCU) with a lagging feedback and topping differentiator (a real differentiating element, RD), with calculating the output according to a PID algorithm and using the actuator model for its implementation, and with calculating the control output speed and using a pulse-width modulator. Formulas for calculating the parameters of the RPCU and RD primary components from the condition of approaching the equivalent PID algorithm are given. The system version with a PID controller with the actuator control proceeding from its model is considered in two options: with individual integrators for the controller's integral component and the actuator model, and with a common integrator for the controller's integral component and the actuator model. In the latter option, the signal from the actuator model is subtracted from the controller's integral component, due to which the possibility of the integrator's output to reach the integral component's limit values is ruled out. The versions are compared by analyzing the automatic control system performance in the pulsed actuator's operation mode based on simulation for the superheated steam temperature control section of a steam boiler equipped with a surface steam desuperheater. The analysis was carried out taking into account both the usual dynamic accuracy indicators and the number of actuators switched into operation during the transient. It is shown that the advantage of the version with the PID algorithm and common integrator for the integral component and the actuator model is that there is no need in this case to calculate the controlled variable second derivative; in addition, this version is free from the problem connected with accumulation of the difference between the signals from the actuator and its model. This version can be considered to be more preferred in implementing a PID algorithm in the software of programmed controllers. Recommendations for self-tuning of pulse duration and the control unit relay element parameters during the control process depending on the algorithm's individual components are given. By using the proposed recommendations, it becomes possible to achieve an essentially lower actuator switching frequency during the control process. [ABSTRACT FROM AUTHOR]

By using LabVIEW (G language), a PID control algorithm was simulated. The designed virtual instrument includes all the necessary components and facilities necessary to function properly and to control any linear process. The issues of integral windup, derivative overrun, output signal limits and sampling interval Δt were treated. The created Sub VI was used as a controller in a closed loop which controls an oven temperature. Results of experiment show a high degree of convergence with the results obtained when an electronic hard-wired controller was utilized [ABSTRACT FROM AUTHOR]

In order to solve the problem of frequent fluctuation of production index caused by the unstable nature of non ferrous metal ores and the related influence of liquid level during the flotation operations. This paper designs a set of automatic control system of flotation liquid level. This system studies the control algorithm of the flotation liquid level loop ? designs the man machine interactive operation interface pertinently? and puts forward a complete set of flotation level automatic control system scheme，which can stabilize the production index of the concentrator? reduce the cost and increase efficiency. The system has been verified the effectiveness of the control system through the comprehensive application of a large scale polymetallic mine in China. [ABSTRACT FROM AUTHOR]

In the field of marine foundation treatment engineering technology, deep cement mixing (DCM) construction method has become one of the main methods for foundation treatment of facilities such as port construction, marine airports, garbage yard and artificial islands. Recently, the first heavy DCM boat with two processors has been independently designed and constructed by domestic units, and the intelligent construction management system was developed. In this paper, the design and implementation of the automatic matching control technology was introduced. According to the construction requirements, the technology can realize intelligent automatic matching of the key parameters such as mixing times, spray flow and lifting speed. It can guarantee the construction quality, and improve the construction efficiency. The current application in the actual engineering construction shows that the method is very effective and stable. [ABSTRACT FROM AUTHOR]

SRAM stability is a major concern in nanometer CMOS technologies. As the most important metrics of SRAM static stability, the static characteristics of SRAM are derived by static characteristic curves (read butterfly curve, standby butterfly curve, read N curve, write N curve and WNM curve). This paper deduces the read butterfly curve transfer function as an example to show the effect of supply voltage deviation. In order to increase the quantity of SRAM DUTs (Device under Tests) and test accuracy, we propose a test method with VDD correction which eliminates the effect of supply voltage deviation. First, an addressable test structure is applied, where the transmission gates are used to force and sense the node voltages, and then correct the voltages. Second, a test algorithm with fast convergence combining the bisection method and PID (Proportion Integral Differential) algorithm is proposed to correct the voltages. SPICE simulations show that the proposed method reduces the error from approximately 10% (commonly used methods) to less than 2%. It is further implemented in a standard 55nm CMOS process, and the static characteristic curves of 1k-bits SRAM DUTs are measured within the accuracy range of 1 mV, which fit well with the simulation results, indicating the method can accurately measure 1k-bits DUTs. [ABSTRACT FROM AUTHOR]

Copyright of Studia Poliana is the property of Studia Poliana 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.)

In this paper, a metaheuristic algorithm called PID-based search algorithm (PSA) is proposed for global optimization. The algorithm is based on an incremental PID algorithm that converges the entire population to an optimal state by continuously adjusting the system deviations. PSA is mathematically modeled and implemented to achieve optimization in a wide range of search spaces. PSA is used to solve CEC2017 benchmark test functions and six constrained problems. The optimization performance of PSA is verified by comparing it with seven metaheuristics proposed in recent years. The Kruskal-Wallis, Holm and Friedman tests verified the superiority of PSA in terms of statistical significance. The results show that PSA can be better balanced exploration and exploitation with strong optimization capability. Source codes of PSA are publicly available at https://ww2.mathworks.cn/matlabcentral/fileexchange/131534-pid-based-search-algorithm. [ABSTRACT FROM AUTHOR]

With the development of the automobile industry, because of their limitations the mechanical devices have been gradually replaced by the electronic ones. The throttle of a car, as a controlled valve to control the air into the engine, is called the throat of engine, and the precision of the throttle can be achieved by the use of an electronic device. In this study, the PID algorithm and sliding mode control algorithm were used on Simulink software to conduct precise tracking control experiments on electronic throttle. The final results demonstrated that the sliding mode control algorithm was superior to the PID algorithm in the control of electronic throttle. The response time and stability time of the sliding mode control algorithm were stable and were shorter than those of the PID algorithm no matter which opening it was. The response time and stability time of the sliding mode control algorithm in this study were 0.1 s and 0.4 s respectively. [ABSTRACT FROM AUTHOR]

In order to reduce the mechanical jitter as recording by cellphones, a 4-DoF (degree of freedom) handheld cloud platform stabilizer which is capable of active anti-vibration is developed. The principle of closed-loop feedback is employed, and various technologies are adopted: 3D printing, micro controller, MEMS (Micro-Electro-Mechanical System), etc. The cloud platform is mechanically realized with one-step forming by 3D printing. Two step motors are utilized to control the motions of roll and pitch, respectively. The cellphone is installed on the stabilizer, 6-axis motion processing sensor acquires the roll and pitch angles of cloud platform. The STM32F407 micro-controller coordinates two step motors by running PID (Proportional-integral-derivative) algorithm. Prototype testing results demonstrate the mechanical vibration is effectively compensated, and the image quality is significantly improved. [ABSTRACT FROM AUTHOR]

The modern power system is a centralized single-power supply system based on large power grids. However, with the popularity of new energy generation technologies, a distributed power generation technology based on new energy has the characteristics of high maintainability and flexible power generation mode. Thus, the mechanism of an analog microgrid control system based on Cortex-M4 controller with real-time measurement and tracking control function was proposed to solve the problems of unsatisfactory load in remote areas and the difficulty of power supply to satisfy the reliability, security, and diversity of power supply. The analog microgrid utilized the principle of three-phase analog microgrid interconnection composed of several grid-connected inverters. The three-phase analog micro-grid generated Alternating Current (AC) signal and other inverters worked in the grid-connected mode and adopted many loop control technologies, such as Proportional-Integral (PI) voltage tracking, PI current tracking, phase-locked loop, and digital feedback (2P2Z) compensation, to operate the grid-connected system in a stable condition. The accuracy of selecting a control algorithm was verified using experimental data. Results demonstrate that the three-phase symmetrical AC generated by an inverter can output 50 Hz sinusoidal current, 24±0.2 V line voltage in load, and =0.03% total harmonic distortion. The adjustment rate when changing the current root mean square of the load is small. The analog microgrid improves the system's instability caused by the complex operation of the microgrid system. The analog microgrid control system also enhances the requirements of hardware protection, such as overcurrent and overvoltage, and designs a software protection for islanding and circulation detections. This study provides references in the fields of system modeling, data processing, and control strategy, which can solve the contradiction between microgrid and power grid and satisfy the requirements of users for power supply. [ABSTRACT FROM AUTHOR]

Copyright of Computer Measurement & Control is the property of Magazine Agency of Computer Measurement & Control 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.)