Fuzzy PID Control Algorithm Research Articles

Discrete fuzzy adaptive PID control algorithm for automotive anti-lock braking system

Due to the low slip rate and poor braking performance of automobile anti-lock braking system, a discrete fuzzy adaptive PID control algorithm for automobile anti-lock braking system is designed in this paper. Based on the theory of discrete fuzzy adaptive PID control algorithm, the braking force of a vehicle is analyzed and the anti-lock control target is set. The automobile adhesion coefficient and wheel slip rate are calculated as the input and output of the PID control algorithm to complete the control of the anti-lock brake system of the network automobile. Experiments show that the sliding rate of the discrete fuzzy adaptive PID control algorithm of the designed anti-lock system is close to 20%, which proves that the design method has good braking effect.

A method to solve the problem of low precision of micro stabilized platform caused by frame coupling - Based on Fuzzy PID

Aiming at the problem of low control efficiency of small stable platform due to frame coupling, an intelligent control algorithm (fuzzy-PID) combining fuzzy controller with traditional PID is designed. The fuzzy PID controller is added to the position closed loop of the stable platform control system, and the motor position signal is collected and analyzed. Compared with the traditional PID control algorithm, the fuzzy PID control algorithm has the advantages of small overshoot, high control precision and strong anti-interference ability. The simulation test in Simulink environment shows that the overshoot of the system is reduced under the algorithm σ, which can be controlled within 1% and the adjusting time t is controlled within 0.5s, which can realize the stable control of the yaw angle, pitch angle and roll angle of the stabilized platform.

Artificial Fuzzy-PID Gain Scheduling Algorithm Design for Motion Control in Differential Drive Mobile Robotic Platforms.

Mobile robots are promising devices which are dedicated to human comfort in all areas. However, the control algorithm of the wheels of mobile robot is entirely challenging due to the nonlinearity. Recently, the classical PID (proportional-integral-derivative) controllers are frequently used in robotics for their high accuracy and the smooth determination of their parameters. A robust approach called fuzzy control which is based on the conversion of linguistic inference sets in a suitable control value is a widely used method in industrial system control in our days. A new challenging method to solve the problem of intelligent navigation of nonholonomic mobile robot is suggested. In this work, the presented methodology is based on three hybrid fuzzy logic PID controllers which are adapted to guarantee target achievement and trajectory tracking. A fuzzy-PID control algorithm is designed with 2 inputs and 3 outputs. By the information given by the system response, error and error derivate can be used to extract and adopt the PID controller parameters: proportional, integral, and derivative gains. Besides, a tuning value A is introduced to improve the resulted response in terms of speeding up and reducing error, overshoot, and oscillation, as well as reducing ISE and IAE values. A modelization of a differential drive mobile robot is presented. The developed algorithm is tested and implemented to this mobile robot model via Simulink/MATLAB.

Iterative Learning‐Based PID Precision Control for Sports Performance Analysis

Traditional function algorithms are contradictory to accuracy and performance. Therefore, taking into account the balance of accuracy and performance, the research of accuracy control‐oriented mathematical function algorithms is of great significance to the design of high‐precision and high‐performance mathematical function algorithms. This paper is aimed at the design of mathematical function algorithm for precision control and has conducted indepth research on traditional PID control algorithm and fuzzy logic control theory. By analyzing the advantages and disadvantages of the two in practical applications, a parameter fuzzy cascade PID control is designed. The algorithm and its performance simulation and comparative analysis provide a theoretical basis for the follow‐up accuracy control algorithm research and realization process. The accuracy control algorithm is then used to calculate and statistically analyze the sports performance including speed, strength (comprehensiveness and explosiveness), endurance, sensitivity, and coordination. The results show that the optimized function random point (nonextreme) test calculation accuracy is 99.5%, and the control accuracy improvement rate of the parameter fuzzy cascade PID control algorithm is about 18.24%. It has better control effect, stronger stability, and higher control accuracy. In the test of extreme points, the optimized test results are obviously better than those before optimization, which can effectively calculate sports results with high accuracy.

Fuzzy pid control of electromechanical actuator system

In order to meet the needs of modern high-performance aircraft, the fuzzy PID control strategy was used to design the electromechanical actuator control system. This control strategy combines the advantages of fuzzy control and PID control, and has better adaptability to time-varying complex systems. The electromechanical actuator control system adopted the three-loop structure, and current loop, speed loop and position loop were built on the platform of MATLAB / Simulink. Considering that the discrete universe fuzzy PID control algorithm has good real-time performance with small online computation, the fuzzy PID controller in discrete universe was designed in the position loop and the system was simulated. The simulation results show that the dynamic and steady performance of discrete universe fuzzy PID control is better than that of traditional PID control, and it is more suitable for electromechanical actuator system.

Design of temperature control system for infant radiant warmer based on Kalman filter-fuzzy PID

In order to improve the dynamic and static performance of the temperature control system of the baby radiant warmer, a Kalman filter-fuzzy PID (KFPID)algorithm is proposed on the basis of the ordinary incremental PID control algorithm. The system uses STM32 as the main controller. The temperature data is collected by the TLV2548 analog-to-digital conversion chip, and the feedback data is filtered by Kalman filter, and the bed surface of the warming table is controlled by the fuzzy PID control algorithm. After the simulation of Matlab, it can be seen that compared with the traditional PID temperature control algorithm, the KFPID algorithm has the characteristics of short adjustment time and almost zero overshoot, and the steady-state error is smaller when dealing with the same interference noise.

Optimal Trajectory Planning and Control for Automatic Lane Change of in Wheel Motor Driving Vehicles on Snow and Ice Roads

In the process of vehicles changing lanes, ice and snow pavement is a very common special working condition, and the research on automatic lane change is usually based on medium and high adhesion coefficient roads. Aiming at the special situation of low adhesion coefficient of ice and snow pavement, this paper studies the process of automatic lane change of vehicles on low adhesion roads driven by the front drive automobile driven by in-wheel motor. First, a dynamic model of a front drive automobile driven by in-wheel motor is established. Then, the trajectory planning is performed based on the fifth-degree polynomial method; the lateral acceleration threshold to ensure the safety of the lane change is deduced; the optimization function of the lane change time and the longitudinal driving displacement is established; and the optimal trajectory to ensure the safety and the lane change efficiency is obtained. Finally, the controller is established based on the fuzzy adaptive PID control algorithm, and the driving torque of the hub motor is distributed through the torque distribution strategy to perform the trajectory tracking control of the vehicle. Simulation results show that the vehicle can safely and smoothly change lanes along the planned trajectory.

Research on Stability Design of Differential Drive Fork-Type AGV Based on PID Control

As one of the important components of intelligent warehousing logistics, Automated Guided Vehicles (AGVs) have greatly improved the efficiency of warehousing operations. AGVs are responsible for the delivery of goods in warehousing and logistics, and it is extremely important to maintain a stable running state. In this paper, an AGV in-situ steering dynamic model is established according to the actual size, and the center deviation phenomenon during AGV steering is theoretically analyzed to obtain the parameters that affect the AGV’s in-situ steering stability. Secondly, the dynamic simulation method is used to analyze the law of the stability of the AGV in-situ steering parameters to verify the correctness of the theoretical derivation equation. According to the analysis results, the motion parameters related to AGV in-situ steering are analyzed, and a reasonable design scheme is given. Based on the optimized fork-type AGV, the AGV in-situ steering control strategy is studied, and the adaptive fuzzy PID control algorithm is used to construct the fork-type AGV steering control system. Then the software and hardware design of the AGV steering control system is carried out. The optimized fork-type AGV has been turned to work stably after commissioning, meeting the actual work requirements.

Global Path Planning and Path-Following for Wheeled Mobile Robot Using a Novel Control Structure Based on a Vision Sensor

This paper presents a novel design for the kinematic control structure of the wheeled mobile robot (WMR) path planning and path-following. The proposed system is focused on the implementation of practical real-time model-free algorithms based on visual servoing. The mainframe of this study is to implement a novel kinematic control structure based on visual sevoing and hybrid algorithms in real-time mobile robot applications. First, the structure of the proposed algorithm based on the visual information extracted from an overhead camera has been addressed. Then, the classification process of robot position and orientation, target, and obstacles has been addressed. Second, the path planning algorithms’ initial parameters and obstacles-free path coordinates have been determined by visual information extracted from images in real time. In this step, the interval type-2 fuzzy inference (IT2FIS) algorithm and various algorithms used in path planning have been compared and their performances have been analyzed. The third stage handled the path-following process using a novel control structure for keeping up the robot on the generated path. In this step, the proposed approach is compared with fuzzy Type-1/Type-2 and fuzzy-PID control algorithms, and their results have been analyzed statistically. The proposed system has been successfully implemented on several maps. The experimental results show that the developed design is valid in generating collision-free paths efficiently and consistently and able to guide the robot to follow the path in real time.

Variable-rate Fertilizer Based on a Fuzzy PID Control Algorithm in Coastal Agricultural Area

Song, L.; Wen, L.; Chen, Y.; Lan, Y.; Zhang, J., and Zhu, J., 2020. Variable-rate fertilizer based on a fuzzy PID control algorithm in coastal agricultural area. In: Yang, Y.; Mi, C.; Zhao, L., and Lam, S. (eds.), Global Topics and New Trends in Coastal Research: Port, Coastal and Ocean Engineering. Journal of Coastal Research, Special Issue No. 103, pp. 490–495. Coconut Creek (Florida), ISSN 0749-0208.Quantitative study on the system of variable-rate fertilizer in agricultural production helps to reduce use of fertilizer, preserve green environment, increase the economic benefit of agriculture, and achieve the sustainable development of agriculture. This study combined the conventional PID control and fuzzy control algorithms with the optimization of genetic algorithm to design the variable-rate fertilizer system. Then, with the prescription map, the speed and swath width of fertilizer application equipment were configurated to accurately control the amount of granular fertilizer applied in a field. The design was mathematically modeled and simulated with the programs of MATLAB (Math Works, Natick, MA). The conclusion as follows: not only do fuzzy control and the PID control based on the combination of genetic algorithm have quicker response speed and robust of anti-parameters change, it achieve high precision control and finally meets the requirement of the experiment purpose. With different quantitative granular fertilizer and speed of tumbrel, the model can well simulate precise control of variable-rate of the granular fertilizer of the tumbrel and uniform fertilizing.

Research on Key Technologies of Elders’ Exoskeleton Robot Assisted by Physical Exercise Based on Fuzzy PID Control

In the past, walking aids (such as crutches and walking aids) widely used by the elderly in physical exercise had relatively single functions, low intelligence, insufficient safety and comfort, and could not meet the needs of users for independent living. Therefore, it is necessary to apply robot technology to the field of traditional walking aid equipment and design a more intelligent, comfortable and safe walking aid robot system. The gait control of the exoskeleton robot assisted by physical exercise for the elderly is studied, and an algorithm based on fuzzy PID is proposed. Firstly, a fuzzy PID control algorithm for the exoskeleton robot assisted by physical exercise for the elderly is given. Secondly, membership functions are selected according to the parameters of the robot joint angle error and error variation. Finally, combined with practical operation experience, a fuzzy rule table is established, and online self-tuning of PID parameters is completed. The experimental results show that the fuzzy PID control method can make the exoskeleton robot move smoothly and realize the gait control of the robot initially.

Study on the Genetic and Fuzzy PID Control Algorithm of Soccer Robot

Study on the Genetic and Fuzzy PID Control Algorithm of Soccer Robot

Study and Application of Fuzzy PID Intelligent Control

In the boiler automatic control system, there are some characteristics of time-varying, large lag and many disturbances in the process of boiler superheated steam temperature control. The traditional PID control cannot achieve the desired control effect, so an intelligent control algorithm called fuzzy PID control is proposed. Fuzzy PID control is based on the PID algorithm, with the error and error rate as input, using fuzzy rules for fuzzy control. By comparing the PID control algorithm with the fuzzy PID control algorithm in MATLAB simulation, the superiority and feasibility of the fuzzy PID control algorithm are verified.

A Compound Control System for FR4-Based Electromagnetic Scanning Micrograting

This paper presents a compound control system for precise control of the flame-retardant 4 (FR4)-based electromagnetic scanning micrograting. It mainly consists of a frequency controller and an angle controller. A dual closed-loop structure consisting of a current loop and an angle loop was designed in the angle controller. In addition, the incremental proportional–integral–derivative (PID) control algorithm was designed in the current loop, and the fuzzy-PID control algorithm was employed in the angle loop. From the experimental results, the frequency controller can effectively track the real-time resonant frequency of the scanning micrograting with a tracking accuracy of 0.1 Hz. The overshoot of the scanning micrograting is eliminated. Compared to an open-loop control system, the control system presented in this work reduces the steady-state error of the scanning micrograting from 1.122% to 0.243%. The control accuracy of the compound control system is 0.02°. The anti-interference recovery time of the scanning micrograting was reduced from 550 ms to 181 ms, and the long-term stability was increased from 2.94% to 0.12%. In the compound control system presented in this paper, the crucial parameters of the FR4-based electromagnetic scanning micrograting, including motion accuracy, anti-interference ability, and long-term stability, were effectively improved.

The design and implementation of a fuzzy gain-scheduled PID controller for the Festo MPS PA compact workstation liquid level control

Due to the high-quality standards required by the process control industry such as liquid-level control, it is desired to implement sophisticated controllers that ensure the proper functioning of the process. Currently most industrial controllers are of the classic PID type. These controllers do a good job in reducing the system error and have simple structure and can be tuned easily when compared to fuzzy gain scheduled PID controllers. However, classic PID controllers do not perform well when the controlled system possesses largely varying dynamics at different operating conditions. Another limitation of classic PID controllers is that their operation depends on the tuning of the proportional, derivative, and integral gains. This paper presents a comparative study between a fuzzy gain scheduled PID controller and a classic PID controller commonly implemented in the process control industry. A comprehensive mathematical model for the Festo MPS PA compact workstation is developed for future use for control system design of the MPS PA compact workstation. Based on the experimental results, the fuzzy gain scheduled PID controller demonstrated supremacy on the PID control strategy. The presented analysis is verified by the implementation of the fuzzy gain scheduled PID control algorithm in the MPS PA compact workstation using custom-built LabVIEW interface. Experimental results verified the effectiveness of the proposed control scheme.

Research on Optimization Retrieval Technology of Multimedia Information Management System Based on Fuzzy Control

In order to improve the efficiency of image information retrieval in multimedia information management system, a retrieval technology of multimedia information management system based on fuzzy directivity control is proposed. The retrieval multimedia information management system is decomposed with LGB to realize the image multimedia information feature compression, and the control constraint parameter model of the multimedia information management system is constructed. The fuzzy directivity control method is used to adjust the retrieval category adaptively, and the edge contour feature quantity of the image in the multimedia information management system is extracted. The fuzzy PID control algorithm is used to cluster and fuse the extracted edge contour features of multimedia images, which can realize the accurate retrieval and scheduling of the images in the multimedia information management system. The simulation results show that the proposed algorithm has high precision and zero frame difference in image retrieval in multimedia information management system, which shows good multimedia information management and system control ability.

Nonlinear Multi-Body Dynamic Modeling and Coordinated Motion Control Simulation of Deep-Sea Mining System

In this paper, a nonlinear integrated multi-body dynamic (MBD) model of a deep-sea mining (DSM) system was developed. A particular nonlinear interaction model between the mining vehicle and the seabed sediment was derived. The fluid resistance and the resistance torque acting on the vehicle were obtained by the computational fluid dynamics (CFD) numerical simulations. In addition, a rigid-flexible coupled discrete element method (DEM) was adopted to model an extremely long mining riser efficiently and accurately. Developed by the C# program, a user-defined subprogram was intended to establish the DEM model of the riser. A motion control system model for trajectory tracking of the vehicle was developed in which the fuzzy control algorithm and the fuzzy adaptive PID control algorithm were used to control the speed and speed ratio of the tracks, respectively. Furthermore, the collaborative simulation between the dynamic model and the control model was achieved, and a coordinated motion mode for the total mining system was proposed and simulated. Accordingly, the trajectory tracking accuracy and slip of the vehicle, the spatial state change of the riser, and the interaction forces among subsystems were analyzed. This paper can provide a valuable theoretical basis and technical reference for the integrated design, performance prediction, and operation control of the practical DSM system.

高精度激光器电流驱动与交流温控系统设计

As an important part of the atomic magnetometer, the semiconductor laser's wavelength and power are mainly determined by current and temperature. However, the traditional DC temperature control system would cause magnetic field interference to the atomic magnetometer. Aiming at high-precision current control, temperature control and magnetic field interference, a laser constant current source driving system and Alternating Current(AC) temperature control system were developed. Firstly, a high-precision laser constant current source driving system based on power amplifier was designed. Secondly, the AC temperature modulation demodulation detection and AC heating drive system were designed. Finally, the STM32 controller, high-precision AD acquisition and DA output combined with temperature fuzzy adaptive PID control algorithm were used for high-precision temperature control. The experimental results show that the temperature control accuracy is 0.005℃ at 42℃, and the current stability is 0.5 A at 32 mA, which lays a foundation for laser optical power and wavelength stability.

Research on Optimization Retrieval Technology of Multimedia Information Management System Based on Fuzzy Control

In order to improve the efficiency of image information retrieval in multimedia information management system, a retrieval technology of multimedia information management system based on fuzzy directivity control is proposed. The retrieval multimedia information management system is decomposed with LGB to realize the image multimedia information feature compression, and the control constraint parameter model of the multimedia information management system is constructed. The fuzzy directivity control method is used to adjust the retrieval category adaptively, and the edge contour feature quantity of the image in the multimedia information management system is extracted. The fuzzy PID control algorithm is used to cluster and fuse the extracted edge contour features of multimedia images, which can realize the accurate retrieval and scheduling of the images in the multimedia information management system. The simulation results show that the proposed algorithm has high precision and zero frame difference in image retrieval in multimedia information management system, which shows good multimedia information management and system control ability.

Study on the Control Strategy of Regenerative Braking for the Hybrid Electric Vehicle under Typical Braking Condition

In this paper, a parallel regenerative braking control strategy and fuzzy PID control algorithm for series-parallel hybrid electric vehicles are developed based on the analysis of the existing regenerative braking control strategy and control algorithm, indicating a reasonable and effective regenerative braking control strategy for series-parallel hybrid vehicles. The simulation model of regenerative braking control system is established by MATLAB/Simulink software, and the parametric model of each component of regenerative braking system is established by AVL CRUISE software. The joint simulation under the typical braking condition of 30, 60 and 90km/h under the moderate braking intensity (z = 0.3) is conducted. The results show that the braking energy recovery rate is the largest (reaching 24%) and the energy recovery effect is obvious in the initial speed of braking of 60km/h.