Fuzzy PID Control Method Research Articles

A Fuzzy Adaptive PID Control Method for Novel Designed Rail Grinding Equipment

Rail defects appear in a greater variety and frequency with the rapid development of High-Speed Rail (HSR), which seriously affects the safe operation of trains. Rail grinding is one of the common methods used to eliminate these defects. However, the quality of rail grinding is often limited by the constant power control method. This paper presents a fuzzy adaptive PID control method based on PID control. In this method, a fuzzy rule library of input and output is established according to the experience of experts and grinding operators, and the PID control parameters can be adjusted in real time through the library to achieve the purpose of constant power grinding. Compared with classical PID, the effectiveness of the proposed method was verified by simulation and the rail grinding experiment with the designed equipment. Experimental results showed that the power data of fuzzy adaptive PID control had less fluctuation, which could be basically stabilized at 5KW±0.1KW, and the curve tracking error was reduced by 60.9%. It is concluded that this method can greatly improve the power accuracy and stability of rail grinding.

A fuzzy PID control method of step response of torque hydraulic mechanical transmission

A fuzzy PID control method of step response of torque hydraulic mechanical transmission

A fuzzy PID control method of step response of torque hydraulic mechanical transmission

A fuzzy PID control method of step response of torque hydraulic mechanical transmission

Research on Attitude Control System of Quadrotor Unmanned Aerial Vehicle based on Fuzzy PID Control Algorithm

The control of quadrotor aircraft mainly includes attitude control and position control. Because the change of position is caused by the change of attitude, it is most important to control the attitude of quadrotor aircraft. PID control principle is simple, easy to master, convenient to use, strong adaptability and good robustness, and its control quality is insensitive to the change of the controlled object, so it is most widely used. Quadrotor UAV is a strongly coupled underactuated system, and its stability is easily affected by system uncertainty and external interference during flight. Therefore, an improved fuzzy PID control method is proposed. In this article, the significance and ideas of constructing the attitude control system of quadrotor UAV based on fuzzy PID control algorithm are analyzed. This control strategy not only keeps the advantages of fuzzy control algorithm, which is independent of accurate model, and flexible and fast control, but also combines the advantages of PID control algorithm with small static error, and can achieve good control of nonlinear complex system.

Research on synchronization of cooperative trajectory of dual industrial robots based on fuzzy adaptive PID control strategy

Through the research on the synchronization of the cooperative trajectory of dual industrial robots, this paper analyses the characteristics of master-slave control and distributed control, and puts forward a fuzzy adaptive PID control method suitable for the cooperative scene of dual industrial robots, which can dynamically adjust the parameters of PID control online and adapt the dynamic system of industrial robots in real time. Taking two same 6-DOF ABB industrial robots as examples, common PID controller and fuzzy PID controller are compared and simulated under master-slave control mode and distributed control mode respectively. The simulation results verified that the fuzzy adaptive PID control method is effective, and the distributed control mode has more applicability and expansibility than the master-slave control mode.

The Brushless DC motor control system Based on neural network fuzzy PID control of power electronics technology

In order to improve The Brushless DC motor control system Based on Particle Swarm Optimization Algorithm with Improved Inertia Weights development of power electronics technology emergence, The brushless director current (DC) motor is a new type of mechatronic motor that has been developed rapidly with the development of power electronics technology, The performance of the brushless DC motor control system, this paper starts with the brushless DC motor to improve the motor structure or use new materials. This paper uses the neural network fuzzy PID control method to carry out the study of the brushless DC motor control system, and chooses the correct control model and control target to solve the influence of the commutation process on the system. Moreover, this paper analyzes and designs the application of model prediction in BLDCM current loop control, and uses this control system to build a simulation model of brushless DC motor control system in MATLAB. The simulation results show that the brushless DC motor control system based on neural network fuzzy PID control can effectively improve the control effect.

EKF-AF PID-Based Attitude Control Algorithm for UAVs

Aiming at the problems of manual setting of control rules and low control accuracy of the fuzzy PID control method, an attitude control method of the unmanned aerial vehicle (UAV) based on the extended Kalman filter (EKF) and adaptive fuzzy PID (AF PID) is proposed. The dynamics equations and measurement equations of UAV are established, and the EKF is used to estimate and predict attitude changes; an adaptive fuzzy PID control algorithm is designed, and the adaptive adjustment method is adopted to revise fuzzy control rules and parameters online; a simulation platform of the attitude control system (ACS) of UAV is built to simulate and verify the control effect of the method. The simulation results show that the proposed algorithm can estimate the change of attitude angles accurately and improve the control accuracy; meanwhile, it also ensures the stability and rapidity of the attitude changes. The research results can resolve the contradiction between high precision and rapid stability of complex systems to a certain extent.

Study on a novel two-part underwater towed system for near-surface towed vehicle test

A new underwater two-part towed system is proposed and studied for the test of near-surface towed vehicles. The near-surface towed vehicle is towed by submarines or the large displacement unmanned undersea vehicle, and plays the role of the communication relay with the onshore station. To deal with the influence of the harsh wave environment and create a stable test platform, a fuzzy-PID control method and an active heave compensation device are applied in the towed system. The mathematical model of the two-part towed system is built. In the model, the nonlinear aspects are considered, such as the interaction of the multi-body, the flexibility of the cable, the wave force, the heave compensation. Based on the model, the simulation results indicate that the Fuzzy-PID control method can significantly reduce the depth fluctuation of the towed vehicle under different sea state. Besides, it is also demonstrated that the active heave compensation device can obviously improve the stability performance of the two-part towed system by greatly reducing the depth fluctuation of the ballast, and create a very stable test environment similar to the submarine or large underwater vehicle.

Fuzzy adaptive PID control method for multi-mecanum-wheeled mobile robot

Fuzzy adaptive PID control method for multi-mecanum-wheeled mobile robot

Optimization of Sorting Robot Control System Based on Deep Learning and Machine Vision

To enhance the control technology of coal gangue dry separation method which is replaced by the machine in coal washing plant and to explore the control effects of traditional PID and dynamic domain fuzzy self-tuning PID, which will aid in determining the ideal position and orientation for grasping an object as well as understanding physical and logistic data patterns, an optimal design of PID controller for sorting robot based on deep learning is initiated. The mathematical model of ball screw system driven by a single joint motor of the robot is introduced, the control effects of classical PID and variable domain fuzzy self-tuning PID are studied and imitated, respectively. The simulation outcome appears that the selection time is 0.001 s and simulation time is 8 s. The tracking error of variable domain fuzzy PID is minor than that of PID tracking at the starting point, and the convergence rate of error is quick than that of PID manage, the steady-state error is minor than PID, the control accuracy is higher, and the tracking performance is better. The advantages of variable domain fuzzy PID control method in position tracking control are verified, the variable domain fuzzy PID can modify the control framework online as per the different position mistake and mistake change rate, the design of the variable domain of input and output makes the fuzzy inference rules locally finer, the speed of adjustment is faster and the tracking accuracy is further improved, so it has finer tracking presentation than the traditional PID tracking management.

An Embedded Linear Model Three-Dimensional Fuzzy PID Control System for a Bionic AUV under Wave Disturbance

This study provides a new embedded linear model (ELM) three-dimensional fuzzy PID control method for a bionic autonomous underwater vehicle (AUV), which is disturbed by ocean waves. The uncertainty of the ocean waves will make it difficult for the AUV to achieve good sailing quality, especially near the sea surface. In view of this problem, an ELM fuzzy PID controller, which adopts three-dimensional fuzzy control rules, is designed. In the ELM fuzzy PID controller, a linear model of AUV is established in order to actively perceive the effect of waves on AUV. Hence, the wave disturbance can be reflected in the control signal earlier and faster. Finally, three simulations are carried out to verify the control effect of the ELM fuzzy PID controller. An ocean wave disturbance model is established in order to simulate the force and the moment acting on the AUV. The results imply that compared with the classical PID controller and normal fuzzy PID controller, the ELM fuzzy PID controller can significantly enhance the stability of AUV and make the response faster and overshoot smaller.

Wheel Deflection Control of Agricultural Vehicles with Four-Wheel Independent Omnidirectional Steering

Due to the harsh working environment of wheeled agricultural vehicles in the field, it is difficult to ensure that all wheels make contact with the ground at the same time, which is easy to unequally distribute the yaw moments of each independent wheel. The commonly used vehicle lateral control methods are mostly controlled by coordinating the individual torque between different wheels. Obviously, this control method is not suitable for agricultural four-wheeled vehicles. The goal of this study was to provide a wheel steering angle control method that uses electric push rods as actuators that can cope with this problem. The design of a four-wheel steering controller generally adopts the linear PID control method, but the research object of this paper is difficult to establish an accurate and linear mathematical model due to the complex working environment. Therefore, fuzzy adjustment is added on the basis of PID control, which can meet the requirements of model difficulty and control accuracy at the same time. In order to verify the feasibility and rationality of the designed wheel steering mechanism, the model dynamics simulation based on ADAMS software and the response analysis of the electric linear actuator thrust were completed. Based on the kinematics model of the controlled object, the rotation angle of the actuator motor is used as the control target, the lateral deviation e and deviation variation ec are taken as input variables and the parameters KP, KI and KD are taken as output variables, thereby establishing a fuzzy PID controller. Then, this controller is constructed in the Matlab/ Simulink simulation environment to analyze the lateral deviation and response stability during the process of vehicle path tracking. From the verification results of the linear path walking test under the fuzzy PID control method, the maximum lateral deviation of vehicle chassis is 2.7 cm when the driving speed is set as 1 m/s, and the deviation adjustment stable time of the system is 0.15 s. It can be seen that the proposed steering control strategy has good response performance and effectively increases the steering stability.

Research on edge controller based on industrial furnace

Traditional control instruments and DCS control systems are limited by shortcomings such as single control function, independent controlled elements, inability to close-loop control on site, and ineffective communication. Aiming at these problems, this paper proposes a kind of industrial furnace edge controller which has the functions of acquisition, calculation, control, storage, output and communication in one. The edge controller structure, edge computing and the control method applied to edge computing are designed. The fuzzy PID control method is compared with the conventional PID control method by taking the temperature control of resistance furnace as an example. The simulation shows that the control effect of fuzzy PID on resistance furnace temperature is obviously better than that of conventional PID. The test results also show that the performance indices for the fuzzy PID control are better, which again proves that the fuzzy PID control outperforms. The research results of this paper are of reference value for engineering applications.

Design of high precision mechatronic-hydraulic leveling system for vehicle-mounted radar

In order to improve the control performance of vehicle-mounted radar, a high precision leveling control system is designed through mechatronic-hydraulic integration technology. A leveling method combining angle error leveling method and height error leveling method is designed, and inclinometers are set in the front and rear of the vehicle body platform to effectively eliminate the virtual outrigger phenomenon in the leveling process. The mathematical model of hydraulic system is developed, the fuzzy PID control method is introduced, and the four-point support hydraulic leveling control system is developed by using STM32 microcontroller as the control core. The field test proves that the control system has good control performance, high leveling accuracy, short time, and meets the control requirements of the radar vehicle.

Application of Fuzzy Neural Network PID In Laser-guided Mortar Projectile

Based on the high control performance requirement of laser-guided mortar control system, the permanent magnet synchronous motor (PMSM) is adopted in this paper as the electromechanical actuator of the system, the mathematical model of the motor is analyzed, and the vector control technology is adopted to achieve precise control of position, speed and torque of the electromechanical actuator. Aiming at the characteristics of non-linearity, strong coupling and large parameter changes of the system in flight, an improved fuzzy neural network PID control method is proposed by combining the classical PID control algorithm with fuzzy control and neural network control algorithm to realize the real-time tuning and optimization of PID parameters. The mathematical model of the electromechanical actuator control system is established and simulated. The results show that the fuzzy neural network PID control has good tracking performance, small amplitude error, and strong adaptability to load changes.

An Improved Fuzzy PID Control Method Considering Hydrogen Fuel Cell Voltage-Output Characteristics for a Hydrogen Vehicle Power System

The hydrogen fuel cell (HFC) vehicle is an important clean energy vehicle which has prospects for development. The behavior of the hydrogen fuel cell (HFC) vehicle power system, and in particular, the proton-exchange membrane fuel cell, has been extensively studied as of recent. The development of the dynamic system modeling technology is of paramount importance for HFC vehicle studies; however, it is hampered by the separation of the electrochemical properties and dynamic properties. In addition, the established model matching the follow-up control method lacks applicability. In attempts to counter these obstructions, we proposed an improved fuzzy (Proportional Integral Derivative) PID control method considering HFC voltage-output characteristics. By developing both the electrochemical and dynamic model for HFC vehicle, we can realize the coordinated control of HFC and power cell. The simulation results are in good agreement with the experimental results in the two models. The proposed control algorithm has a good control effect in all stages of HFC vehicle operation.

Braking Control System of Oilfield Minor Repair Machine Based on Wireless Sensor Network

Traditional minor repair machines have low control efficiency and low automation. In order to improve the brake control efficiency of the oilfield minor repair machine, the oilfield minor repair machine brake control system based on wireless sensor network is designed. The front-end controller collects the data of the oilfield repair machine through the wireless sensor and realizes the communication between the sensor nodes and the data interaction with the communication node through the field bus inside the equipment. The server uploads the processed data through the 3G network, and the server receives the data from the front-end controller and saves it in the database. The remote-control center accesses the server through the Internet to view the front-end controller data. The brake control module uses the expert fuzzy PID control method to control the speed, oil pressure, and operating status of the oilfield minor repair machine and sends the data to the front-end control center to complete the oilfield minor repair remote-control machine by sending control instructions. Experimental results show that the system can meet the braking control requirements of oilfield minor repair machines, the output can quickly track input changes, the braking control effect is good, the dynamic deviation of the machine can be reduced, and the braking control efficiency can be improved.

Research on Double Hanging Point Hydraulic Synchronous Control System Based on Fuzzy PID

Hydraulic hoist is required to open and close the gate. In recent years, scholars have studied a lot of different types of hydraulic hoist, in which the double point hydraulic hoist is one of them. Double point crane hydraulic hoist mainly uses the hydraulic synchronous system. In this paper, the hydraulic synchronous system as the research object, through the electrohydraulic proportional speed control valve research, analysis of its working principle. Then, the traditional PID control method and the fuzzy PID control method are compared and analyzed. It is found that the fuzzy PID control ability is better than the traditional PID control method. Fuzzy PID realizes hydraulic synchronization by adjusting the electro-hydraulic ratio of speed control valve.

Modeling and Research of Fuzzy PID Control Strategy for Hydraulic Rock Drill Propulsion System

According to the coupling characteristic of propulsion system and impact system of hydraulic rock drill, deduced the calculation formula of optimal axial thrust for the propulsion system of hydraulic rock drill. On the basics of the calculation formula before, the paper constructed compound driven propulsion system of hydraulic rock drill based on electro-hydraulic proportional pressure-reducing valve and high speed on-off valve, and established its dynamics model. Finally, the paper considered optimal axial thrust as the goal, and adopted the fuzzy PID control strategy to realize on-line, intelligent control to axial thrust of the propulsion system of hydraulic rock drill. Through mathematical modelling and simulation study show that fuzzy PID control method has its advantages as the fast response follow by target, high control precision, and small fluctuation, and provided theory reference and technology method for intelligent control of the propulsion system of hydraulic rock drill.

Analysis of Thermal Characteristics of Airborne Integrated Environmental Control System

Taking the simplified airborne integrated thermal management system as the research object, the change characteristics of the system under different control modes are analyzed, which provides a theoretical basis for the study of system control schemes. Using a combination of mathematical models and computer models to establish an integrated airborne thermal management system model with fuel as the main heat sink, air/fuel heat exchanger, fuel/PAO heat exchanger and other main components, and A fuzzy self-tuning PID control method is proposed to analyze system characteristics such as fuel/PAO heat exchanger and electronic equipment thermal changes. The results show that compared to open-loop control under thermal extreme conditions, the fuzzy self-tuning PID control mode can not only effectively control a series of equipment such as fuel pumps to maintain proper speed, but also ensure the electronic cabin and fuel/PAO heat exchanger the outlet temperature is kept within a predetermined range to meet the design requirements of the onboard thermal management system.