Fuzzy PID Control Method Research Articles

Modeling and Regulation of Dynamic Temperature for Layer Houses Under Combined Positive- and Negative-Pressure Ventilation

The environmental control of layer houses with multi-tiered cage systems is influenced by factors such as the structure of the henhouses and the heat dissipation of the flock, leading to low precision and large fluctuations in temperature control. Based on a new combined positive- and negative-pressure ventilation (CPNPV) mode, a dynamic temperature model is constructed. Additionally, a temperature control method for a layer house is designed using a variable universe fuzzy PID control algorithm (VFPID). First, based on the principles of energy and mass balance, and by decoupling the relationship between positive- and negative-pressure ventilation volumes, a dynamic temperature model for layer houses under CPNPV was established. Then, the PID parameters and the proportional relationship between positive- and negative-pressure ventilation were optimized through fuzzy rules, and a proportional exponential function was introduced to adjust the scaling of the universe, enabling fine-tuned control. Finally, a temperature control model for the layer house was built using Simulink. The results show that the coefficients of determination (R2) of the constructed dynamic temperature models are between 0.79 and 0.88, respectively, indicating high accuracy. The designed VFPID method outperformed traditional on–off control and improved control precision by 20–23.53% and 10.34–22.22% compared with PID control and fuzzy PID(FPID) control methods, respectively. This study provides new insights for the development of environmental control equipment and precise environmental regulation of layer houses.

Advanced Study: Improving the Quality of Cooling Water Towers’ Conductivity Using a Fuzzy PID Control Model

Cooling water towers are commonly used in industrial and commercial applications. Industrial sites frequently have harsh environments, with certain characteristics such as poor air quality, close proximity to the ocean, large quantities of dust, or water supplies with a high mineral content. In such environments, the quality of electrical conductivity in the cooling water towers can be significantly negatively affected. Once minerals (e.g., calcium and magnesium) form in the water, conductivity becomes too high, and cooling water towers can become easily clogged in a short time; this leads to a situation in which the cooling water host cannot be cooled, causing it to crash. This is a serious situation because manufacturing processes are then completely shut down, and production yield is thus severely reduced. To solve these problems, in this study, we develop a practical designation for a photovoltaic industry company called Company-L. Three control methods are proposed: the motor control method, the PID control method, and the fuzzy PID control method. These approaches are proposed as solutions for successfully controlling the forced replenishment and drainage of cooling water towers and controlling the opening of proportional control valves for water release; this will further dilute the electrical conductivity and control it, bringing it to 300 µS/cm. In the experimental processes, we first used practical data from Company-L for our case study. Second, from the experimental results of the proposed model for the motor control method, we can see that if electrical conductivity is out of control and the conductivity value exceeds 1000 µS/cm, the communication software LINE v8.5.0 (accessible via smartphone) displays a notification that the water quality of the cooling water towers requires attention. Third, although the PID control method is shown to have errors within an acceptable range, the proportional (P) controller must be precisely controlled; this control method has not yet reached this precise control in the present study. Finally, the fuzzy PID control method was found to have the greatest effect, with the lowest level of errors and the most accurate control. In conclusion, the present study proposes solutions to reduce the risk of ice-water host machines crashing; the solutions use fuzzy logic and can be used to ensure the smooth operation of manufacturing processes in industries. Practically, this study contributes an applicable technical innovation: the use of the fuzzy PID control model to control cooling water towers in industrial applications. Concurrently, we present a three-tier monitoring checkpoint that contributes to the PID control method.

PCR virtual temperature sensor design based on system modeling and identification

The reaction results of Polymerase chain reaction (PCR) are highly sensitive to temperature accuracy, but the reaction liquid temperature is hard to be measured directly. In this paper, a virtual temperature sensor is creatively designed to directly obtain the reaction liquid temperature using a model-switching approach. This study first establishes the mathematical models of the temperature control system and obtains precise system models for the heating and cooling stages. Based on this, a virtual sensor is constructed, and a closed-loop fuzzy PID control system is established. Furthermore, the accuracy of the designed virtual temperature sensor is verified through simulation and experimentation. Simulation results show that the fuzzy PID control method has higher temperature accuracy, with a deviation of 0.23 °C, making it more suitable for Peltier systems, as Peltier systems suffer from inconsistent temperature rise and fall models. The experimental results show that the control method using the virtual sensor achieves higher precision in liquid temperature control, with an accuracy of ±0.21 °C. Finally, standard PCR procedures are performed for designed chip, and the results indicate that the temperature sensor and control system designed in this study exhibit significantly higher amplification efficiency, approximately 16 times greater than traditional control methods.

Design of intelligent cruise control system using fuzzy-PID control on autonomous electric vehicles prototypes

Electric vehicles provide a solution for using alternative fuels, namely, electricity. Electric vehicles are used for short distances and intercity travel over long distances, increasing the risk of accidents. Cruise Control is a technology embedded in vehicles to maintain stable speeds; this system will automatically adjust the vehicle's speed when motion changes cause changes in vehicle speed. This study aims to apply lidar sensors to detect distance in the Intelligent Cruise Control (ICC) system using the Fuzzy-PID control method. Testing results were obtained at safe distance inputs of 5, 6, and 7 meters with various object distances. All the tests were carried out; the response systems were obtained with an average settling time of 5 seconds and an average overshoot of 1.53%. Therefore, the proposed Fuzzy-PID method works well for controlling Intelligent Cruise Control systems in autonomous electric vehicle prototypes.

Research on charging strategy based on improved particle swarm optimization PID algorithm

Aiming at the electric vehicle charging pile control system has the characteristics of multi-parameter, strong coupling and non-linearity, and the existing traditional PID control and fuzzy PID control methods have the problems of slow charging speed, poor control performance and anti-interference ability, as well as seriously affecting the service life of the battery, this paper designs a kind of improved particle swarm algorithm to optimize the PID controller of the charging control system for electric vehicle charging piles, and utilizes the improved particle swarm algorithm to Adaptive and precise adjustment of proportional, integral and differential parameters, so that the system quickly reaches stability, so as to improve the accuracy of the system control output current or voltage. Simulation results show that the optimized system response speed of the improved particle swarm algorithm is improved by 3.077 s, the overshooting amount is reduced by 1.01%, and there is no oscillation, which has strong adaptability and anti-interference ability, and can significantly improve the control accuracy and charging efficiency of the charging pile control system.

Research on the cabin pressure control system based on the gray wolf fuzzy PID algorithm

The cabin pressure control system is typically nonaffine-nonlinear time-varying system. In this paper, the fuzzy PID control method optimized by gray wolf algorithm is proposed to solve the problems of large overshoot and long adjustment times in traditional control methods. Simulation results show that the fuzzy PID control method optimized by gray wolf algorithm proposed in this paper improves the dynamic characteristics of the system, reduces cabin pressure error and adjustment time, stabilizes the control process, and improves the comfortableness of passengers.

Liquid Level Control System for Degassing Chamber of Vacuum Oil Filter Based on Fuzzy PID

This paper proposed a fuzzy PID control method to address the complexities associated with the inertia and nonlinear variations in liquid level control within the degassing chamber of vacuum oil filter. Tailored to meet practical control demands, a fuzzy control rule table was devised. This solution was simulated and applied in MATLAB/Simulink. The results indicated that, in comparison to classic PID, fuzzy PID exhibited faster adjustment speed and reduced overshoot, making it a more suitable option for vacuum oil filter applications.

Modeling and braking analyses of longitudinal-vertical coupling towbarless aircraft taxiing system

The variation of tire vertical load has effects on the vehicle braking performance, which may lead to the misjudgment of braking distance and increasement of the accident risks. In order to evaluate the braking distance of the towbarless aircraft taxiing system (TLATS) accurately, a longitudinal-vertical coupling model of the TLATS is established, in which the effects of the vertical vibration on braking dynamics is considered. An 11-degrees of freedom (DOF) dynamic model of the TLATS, which consists of the system longitudinal motion, vertical vibration, and an advanced Lugre tire model, is proposed. The tire vertical dynamic loads are obtained by calculating system vibration differential equations as the input for the Lugre tire model, in which an arbitrary pressure distribution function over the contact patch and load related parameters are used. The Lugre tire model parameters are identified based on the virtual experiment results in ADAMS/Car software through a multi-objective optimization (MOO) method. The proposed tire model is more accurate by comparing with the models using other pressure distribution functions. The advanced Lugre model is integrated into the longitudinal-vertical coupling dynamic model of the TLATS, and the fuzzy PID control method is used to achieve the optimal slip rate during the braking procedure. The tire friction and TLATS’s braking performances in terms of the slip rate, braking speed and braking distance are compared between the coupling and uncoupling models under different traction velocities and the road excitations when a same fuzzy control method is used for the system braking. The results show that the proposed longitudinal-vertical coupling TLATS dynamic model could assess the braking behaviors of the TLATS more accurately than the simplified uncoupling model, which could decrease the potential safety risk of the aircraft towing operation on the airport apron.

Process Optimization for Robotic Ultrasonic Strengthening of Aviation Blade Surfaces Based on Intelligent Compliance Control.

In order to enhance the automation level and achieve high precision in the ultrasonic strengthening of aviation blade surfaces, this study focuses on investigating the intelligent control strategy and optimizing the machining parameters for robotic ultrasonic surface strengthening. By designing an intelligent compliance control method, the end-effector can achieve the compliant output of contact force. The fuzzy PID control method is used to optimize the regulation performance of the compliant force control system. This compliance control strategy enables the optimization of the compliance device, effectively improving the static and dynamic characteristics of the compliance controller. Based on this, an experimental method (RSM) is designed to analyze the interaction effects of contact force, feed rate, and repetition times on the surface quality of the blade. The optimal combination of robotic strengthening parameters is determined, providing a practical reference for the application of robotic compliance control in the ultrasonic strengthening of aviation blade surfaces.

Control Strategy of New Energy Vehicle Interior Thermal Management System Based on Intelligent Assisted Algorithms

<p>Reasonable and efficient utilization of pure electric vehicle thermal management system can improve the battery utilization rate of new energy vehicles, thereby increasing the vehicle’s range and charging anxiety. This article proposes a new tram thermal management system scheme for temperature management in new energy vehicles, and designs corresponding thermal management system control strategies based on fuzzy adaptive PID control method. Finally, in order to verify the effectiveness of the management plan and control strategy, Matlab software was used for simulation. The simulation results showed that the intelligent control method proposed in this paper can increase the battery utilization rate by 17%.</p> <p> </p>

Research on Hydro-pneumatic Suspension Test Bench Based on Electro-hydraulic Proportional Control

Compared with the traditional automotive suspension, hydro-pneumatic suspension has the characteristics of large energy storage ratio, nonlinear stiffness and can change the ground clearance of the vehicle body, which makes the vehicle have good ride comfort and handling stability during driving. In order to improve the performance of hydro-pneumatic suspension, it is necessary to design hydro-pneumatic suspension test bench for performance test. Aiming at the problem that the output signal of the mechanical test bench used in China is single and has large error, which is difficult to meet the performance test requirements of hydro-pneumatic suspension, a hydro-pneumatic suspension test bench based on electro-hydraulic proportional control is designed. Through AMESim/MATLAB joint system modeling and simulation, in the tracking comparison of sinusoidal signal, compared with the traditional PID control method, the fuzzy PID control method reduces the error by 56.8% and the lag time by 70%; Through the experimental analysis of hydro-pneumatic suspension elastic force characteristic diagram, indicator diagram and damping force velocity characteristic diagram, the error rate of the test bench in sinusoidal signal tracking experiment is less than 15%, which meets the test requirements of hydro-pneumatic suspension.

An intelligent integrated EDI module based on fuzzy PID

Electrodeionization (EDI) is a popular method of water treatment in the current field of water treatment. EDI module mainly absorbs the charged ions in water through the cation exchange resin and realizes the ion removal of water by applying an electric field to make the charged ions move in a directional way and pass through the cation exchange membrane with selective permeability. The existing EDI module has a low integration degree and the working current cannot be adjusted intelligently according to the field environment. In order to solve the problem of low integration degree, this paper designs an EDI module that integrates the EDI module, sensor, controllable constant current source module, and main controller. Meanwhile, in order to solve the problem that the current EDI working current cannot be adjusted in real-time with the environmental water quality, an EDI module output current control method based on fuzzy PID and a main controller hardware circuit based on the adjustable constant current source circuit of a microcontroller digital-to-analog converter (DAC) are designed to adjust the output current of EDI module intelligently. Then the control model of the control system is established by Matlab respectively using the PID control method and fuzzy PID control method, and the simulation is compared. In this paper, the hardware and software of the module are developed based on STM32. The experimental results show that the designed EDI module can realize accurate and fast control of water quality.

Temperature Regulation of Hot Vapor Preservation Treatment of Litchi Based on PSO-Fuzzy PID

In this paper, a control method was designed based on particle swarm optimization (PSO)–fuzzy PID (PSO-Fuzzy PID). In order to address the issues of significant nonlinearity and extensive hysteresis in the vapor temperature of litchi hot vapor preservation treatment equipment, as well as the inadequacy of traditional control schemes, a PSO-Fuzzy PID controller was developed through the integration of particle swarm optimization and fuzzy logic algorithms. This controller incorporates a scale factor and quantization factor, building upon the foundation of the Fuzzy PID controller. Additionally, a transfer function model was established for both the heating and disturbance links, utilizing a combination of test data modeling methods and relevant theory. Thirdly, a system simulation model was built to compare and verify PID, Fuzzy PID, and PSO-Fuzzy PID control methods, which were carried out on the MATLAB/Simulink simulation platform. Finally, the litchi load test was conducted to further verify the control performance of the PSO-Fuzzy PID method, where the litchi variety was “Jinggang Hongnuo”. The simulation results showed that the overshoot of the optimized control system was reduced by 93.5% and 42.9% compared with the traditional PID control and Fuzzy PID, and the regulation time was shortened by 46% and 31%, which indicates a better control effect. The test results showed that PSO-Fuzzy PID showed better system stability and accuracy than the fuzzy PID control method in different processing temperature and processing time for litchi’s hot vapor treatment. The maximum temperature difference decreased by 0.56 °C on average and the interference adjustment time was reduced by 7.5 s on average. PSO-Fuzzy PID has a good control effect on the temperature of litchi hot vapor treatment, which can provide a reference for model building and temperature control of other similar fruit and vegetable heat treatment equipment.

PID control of evaporation temperature control system based on fuzzy RBF neural network

In this thesis, a fuzzy RBF neural network PID (RBFfnn-pid) control method is designed for temperature deviation concerning the steam curing temperature control system in the steam curing kettle of the aerated concrete block production line. The temperature control system (TCS) models of steam curing are established respectively under the control of fuzzy PID and RBFfnn-pid. Then, the control effect is analyzed by simulation in different situations. The results show that, under this condition of step signal inputting, the RBFfnn-pid control method shortens the rising time by 160 s and reduces the overshoot by 8% compared with the fuzzy PID controlling means. When the system is in a stable state, then the interference signal is added, which in contrast to the controlling means of fuzzy PID, the time for adjusting the RBFfnn-pid control to the set value is shortened by 70 seconds and there is no overshoot. The RBFfnn-pid control method enables the controlling parameters of the steaming temperature control system to be adjusted to the optimum quickly and iteratively, which improves the temperature control accuracy.

Vibration characteristics control of hybrid radial gas foil bearing-rotor system: Simulation and experiment

Currently, tiny, high-speed rotating machines frequently employ air foil bearings. Air is employed as the working medium, however, when the rotor speed is high, the rigidity of the air film is insufficient, which restricts the usage of air foil bearings. This study utilizes the external gas supply method of hydrostatic gas bearings to strengthen the air film stiffness of air foil bearings. The original air foil bearings are combined with external gas supply piping to create the hybrid gas foil bearing(HGFB), which may be utilized to increase the air film support stiffness of the bearings through the external gas supply. Additionally, by altering the gas supply pressure, this bearing may be used to actively manage the vibration characteristics of the shaft system, allowing the bearing performance to be adjusted to changing operating conditions. The static and dynamic properties of the HGFB with a 24 mm diameter are solved in this study using Newton's iterative approach and the finite difference method. The bearing-rotor system is modeled using this information. An Analysis is done on the impact of various air supply pressures and throttle hole widths on bearing performance and vibration characteristics of the shaft system. In this article, the vibration parameters of the bearing-rotor system are tested using an open-loop control test. The open-loop control experiment on the vibration response of the bearing-rotor system is performed using HGFBs with orifice sizes of 0 mm, 0.2 mm, 0.4 mm, 0.6 mm, 0.8 mm, and 1.0 mm. The experimental results confirm the accuracy of the simulation results. Correspondingly, this paper conducted closed-loop control comparison experiments on the vibration properties of the bearing-rotor system using the PID control method and the fuzzy PID control method in succession. It then evaluated the control effect of the two control strategies on the vibration of the bearing-rotor system and managed to improve the conventional PID control method used for gas bearings.

Membrane humidity control of proton exchange membrane fuel cell system using fractional-order PID strategy

Dynamic humidity control is a crucial factor affecting the working performance of proton exchange membrane fuel cell (PEMFC) system. Proper membrane humidity can guarantee power generation performance, improve energy utilization efficiency, prevent irreversible degradation of the proton exchange membrane (PEM). In this paper, a dynamic control model for PEMFC humidity management is proposed, and a fractional-order PID (PIλDμ) control strategy is introduced to balance the membrane humidity of PEMFC. The results show that comparing with traditional PID control methods, the PIλDμ control shows shorter response time, lower overshoot in membrane humidity control, and higher power generation efficiency in PEMFC system. In addition, the performance of the PEMFC using PIλDμ control method at different pressure and temperature conditions is discussed. The power generation efficiency of the PEMFC under PIλDμ control is improved, which is 2.1 %, 3.9 % higher than that of fuzzy PID and conventional PID control method.

Anti-Overturning Capability and Fuzzy PID Speed Control for Four-Way Shuttle Vehicles in Processed Grain Storage

As the four-way shuttle vehicle is prone to overturning in finished grain storage during acceleration and deceleration, an overturning mechanical model is constructed. The design factors analyzed include grain bag height, vehicle and grain bag mass, and the type of grain’s effect on the vehicle’s anti-overturning stability. The critical overturning condition of the shuttle vehicle during operation is also determined as a result of this analysis. With the critical overturning condition, the speed control of the shuttle vehicle based on the fuzzy PID method is carried out to improve the anti-overturning stability. Significant details are made about the fuzzification of input and output variables, determination of membership function, establishment of the fuzzy rule base, fuzzy reasoning, and defuzzification. Finally, the comparative simulation model of fuzzy PID and conventional PID in the MATLAB/Simulink platform showed that the fuzzy PID control method had the advantages of fast convergence and quick response to the speed control of the four-way shuttle vehicle.

An Improved Differential Evolution Adaptive Fuzzy PID Control Method for Gravity Measurement Stable Platform.

In the platform gravimeter, the stabilization accuracy of the gravimetric stabilization platform is crucial to improve the accuracy of gravity value measurements due to its uncertainties, such as mechanical friction, inter-device coupling interference, and nonlinear disturbances. These cause fluctuations in the gravimetric stabilization platform system parameters and present nonlinear characteristics. To resolve the impact of the above problems on the control performance of the stabilization platform, an improved differential evolutionary adaptive fuzzy PID control (IDEAFC) algorithm is proposed. The proposed enhanced differential evolution algorithm is used to optimize the initial control parameters of the system adaptive fuzzy PID control algorithm to achieve accurate online adjustments of the gravimetric stabilization platform's control parameters when it is subject to external disturbances or state changes and attain a high level of stabilization accuracy. The results of simulation tests, static stability experiments, and swaying experiments on the platform under laboratory conditions, as well as on-board experiments and shipboard experiments, all show that the improved differential evolution adaptive fuzzy PID control algorithm has a higher stability accuracy compared with the conventional control PID algorithm and traditional fuzzy control algorithm, proving the superiority, availability, and effectiveness of the algorithm.

Transmission Line Condition Monitoring Method Based on Binocular Vision and Edge Computing for Line Changing Robot

Efficient and accurate state detection of transmission cables is an important means to ensure reliable transmission. Aiming to realize fast and efficient transmission cable state analysis with the help of a binocular vision tool on a loop dismantling robot, this paper proposes a transmission cable state recognition method combining motion control and image segmentation technology. In this method, the fuzzy P I D control method is adopted to ensure that the wire removal robot can realize high-precision and rapid response control and effectively improve the collection quality of the cable image sample set. Meanwhile, aiming to achieve faster and more efficient data acquisition and state analysis, the state analysis model is sunk to the edge side, and the cable state detection and recognition model is constructed based on the fast RCNN model at the edge of the network to realize the in-depth extraction of feature information, enhance the transmission cable state recognition effect of the state detection model, and improve the response analysis speed of the model. The simulation results show that the accuracy of the proposed method is 97.54%, and its calculation time is 1.034 s, which can effectively realize the analysis and research of transmission cable state under complex working conditions.

Speed Control of Secondary Regulation Heave Compensation Based on Fuzzy PID

Aiming at the problem that the widely used heave compensation technology is difficult to balance the compensation effect and energy consumption, based on the secondary regulation technology, the fuzzy PID control method is selected to design a winch heave compensation system with energy recovery. Firstly, a mathematical model is established and analyze the energy-saving characteristics of the heave compensation system. Then, the swash plate controller and speed outer loop controller are designed, and the simulation is model with the AMESim-MATLAB co-simulation platform. Finally, the simulation results are tested by experiments. And the test result reflects that the compensation efficiency of the compensation is more than 90%, and part of the energy can be recovered. The controller has good control accuracy and stability. The compensation system can effectively compensate for the position deviation caused by waves, thus providing a safety guarantee for offshore operations.