scholarly journals INTELLIGENT CONTROL TECHNOLOGY OF AGRICULTURAL GREENHOUSE OPERATION ROBOT BASED ON FUZZY PID PATH TRACKING ALGORITHM

2020 ◽  
pp. 181-190
Author(s):  
Ren Qun
Keyword(s):  
Control System ◽  
Pid Control ◽  
Fuzzy Controller ◽  
Good Control ◽  
Path Tracking ◽  
Tracking Algorithm ◽  
Practical Significance ◽  
Fuzzy Pid ◽  
Path Tracking Algorithm

With the development of agricultural automation, applying intelligent algorithms to the navigation control of agricultural work vehicles has important practical significance for improving vehicle navigation accuracy and operation efficiency. In view of the complexity of the agricultural greenhouse environment, this study proposed a fuzzy PID path tracking algorithm based on the traditional vehicle PID control system. This algorithm uses a fuzzy controller to improve the PID control system, thereby realizing the online setting of PID control parameters. In order to verify the effectiveness of the fuzzy PID path tracking algorithm, the improved control system was applied to the tracked vehicle robot of Beijing Forestry University, and the operation performance of the vehicle robot was tested. The research results show that the absolute error rate of vehicle robot distance measurement is less than 1%; the error of the man-machine follow-up test is between 4 and 7 cm, and the measured follow-up distance is slightly less than the safe follow-up distance; the maximum error of the vehicle's fixed-point parking is 0.3 cm; The linear position tracking control has a lateral position deviation of ±3cm, and the vehicle's linear driving control and steering effects are better. The fuzzy PID path tracking algorithm designed this time shows good control performance, which has reference significance for the practical application of agricultural robots.

The Design and Simulation of Control System for Electrical Heating

2013 ◽  
Vol 325-326 ◽  
pp. 1193-1196
Author(s):  
Guo Sheng Xu
Keyword(s):  
Control System ◽  
Pid Control ◽  
Fuzzy Controller ◽  
Electrical Heating ◽  
Temperature Control System ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Adaptive Fuzzy ◽  
Fuzzy Pid Controller ◽  
Electric Boiler

In view of the fact that the performance of any conventional PID control can t meet the requirement an electric boiler temperature control system, this paper puts forward a kind of improved algorithm for tuning the PID parameters. an adaptive fuzzy controller with adjusting factor is proposed in this paper. Experimental results illustrate that the adaptive fuzzy PID controller achieved the system performance index. The method of adaptive fuzzy PID control is a ideal method.

scholarly journals Design of and Research into a Multiple-Fuzzy PID Suspension Control System Based on Road Recognition

Processes ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 2190
Author(s):  
Xinkai Ding ◽  
Ruichuan Li ◽  
Yi Cheng ◽  
Qi Liu ◽  
Jilu Liu
Keyword(s):  
Control System ◽  
Pid Control ◽  
Good Control ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
The Road ◽  
Suspension Control ◽  
Neural Network Algorithm ◽  
Road Grade ◽  
Differential Control

By analyzing the shortcomings of the traditional fuzzy PID(Abbreviation for Proportional, Integral and Differential) control system (FPID), a multiple fuzzy PID suspension control system based on road recognition (MFRR) is proposed. Compared with the traditional fuzzy PID control system, the multiple fuzzy control system can identify the road grade and take changes in road conditions into account. Based on changes in road conditions and the variable universe and secondary adjustment of the control parameters of the PID controller were carried out, which makes up for the disadvantage of having too many single input parameters in the traditional fuzzy PID control system. A two degree of freedom 1/4 vehicle model was established. Based on the suspension dynamic parameters, a road elevation algorithm was designed. Road grade recognition was carried out based on a BP neural network algorithm. The experimental results showed that the sprung mass acceleration (SMA) of the MFRR was much smaller than that of the passive suspension system (PS) and the FPID on single-bump and sinusoidal roads. The SMA, suspension dynamic deflection (SDD) and tire dynamic load (TDL) of the MFRR were significantly less than those of the other two systems on roads of each grade. Taking grade B road as an example, compared with the PS, the reductions in the SMA, SDD and TDL of the MFRR were 40.01%, 34.28% and 32.64%, respectively. The control system showed a good control performance.

Fuzzy PID Control System for Sludge Digestion Tank Temperature

2014 ◽  
Vol 496-500 ◽  
pp. 1221-1225 ◽  
Author(s):  
Shu Qi Xue ◽  
Wen Zhao Yan ◽  
Liang Ma
Keyword(s):  
Control System ◽  
Temperature Control ◽  
Pid Control ◽  
Fuzzy Controller ◽  
Self Regulation ◽  
Pid Controllers ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Sludge Digestion ◽  
Fuzzy Control Algorithm

In order to improve the accuracy and stability of sludge digestion tank temperature control, based on the PID control with fuzzy controller, using the fuzzy control algorithm, obtained the adjustment of PID control parameters and online self-regulation of PID controllers parameters. The simulation tests show that the fuzzy PID control system for sludge digestion tank temperature outperforms the general PID control system because of a ±1°C control accuracy, this can satisfy the requirements of temperature control of sludge digestion.

Design of Compound Fuzzy Controller for Multivariable Systems

2009 ◽  
Vol 16-19 ◽  
pp. 150-154 ◽  
Author(s):  
Xue Ming Zhang ◽  
Gui Xiang Zhang ◽  
Feng Shao ◽  
Qing Jie Yang
Keyword(s):  
Control System ◽  
Pid Control ◽  
Pid Controller ◽  
Fuzzy Controller ◽  
Design Method ◽  
Design Procedure ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Fuzzy Pid Controller ◽  
Tuning Rules

The PID controllers can be seen in lots of fields, but some complex control system cannot be controlled to achieve a desired performance index. A design method of the fuzzy PID controller that is based on the fuzzy tuning rules and formed by integrating two above control ideas is proposed in this paper. The design procedure about fuzzy PID control can be divided two steps: the first step is to build the fuzzy tuning rules by analysis, and to obtain the parameters of PID controller by reasoning, and then the control action can be determined by the PID control law. The simulation results and the practical control effects show that the compound fuzzy PID controller has better performance than that of the conventional PID control system and meet the practical demands.

Path Tracking Controller Design of Automatic Guided Vehicle Based on Four-Wheeled Omnidirectional Motion Model

2020 ◽  
Vol 17 (2) ◽  
pp. 7996-8010
Author(s):  
X. Wu ◽  
Y. Yang
Keyword(s):  
Control System ◽  
Fuzzy Controller ◽  
Controller Design ◽  
Threshold Value ◽  
Position Angle ◽  
Path Tracking ◽  
Global Coordinate System ◽  
Automatic Guided Vehicle ◽  
Input Variables ◽  
Industrial Pc

This paper presents a new design of omnidirectional automatic guided vehicle based on a hub motor, and proposes a joint controller for path tracking. The proposed controller includes two parts: a fuzzy controller and a multi-step predictive optimal controller. Firstly, based on various steering conditions, the kinematics model of the whole vehicle and the pose (position, angle) model in the global coordinate system are introduced. Secondly, based on the modeling, the joint controller is designed. Lateral deviation and course deviation are used as the input variables of the control system, and the threshold value is switched according to the value of the input variable to realise the correction of the large range of posture deviation. Finally, the joint controller is implemented by using the industrial PC and the self-developed control system based on the Freescale minimum system. Path tracking experiments were made under the straight and circular paths to test the ability of the joint controller for reducing the pose deviation. The experimental results show that the designed guided vehicle has excellent ability to path tracking, which meets the design goals.

Intelligent Information of TS Fuzzy PID Control System of BLDCM

2013 ◽  
Vol 846-847 ◽  
pp. 313-316 ◽  
Author(s):  
Xiao Yun Zhang
Keyword(s):  
Control System ◽  
Dynamic Model ◽  
Pid Control ◽  
Control Method ◽  
Design Method ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Control Precision ◽  
Simulation Results ◽  
Intelligent Information

This paper presented a new method based on the Fuzzy self - adaptive PID for BLDCM. This method overcomes some defects of the traditional PID control. Such as lower control precision and worse anti - jamming performance. It dynamic model of BLDCM was built, and then design method for TS fuzzy PID model is given, At last, it compared simulation results of PID control method with TS Fuzzy PID control method. The results show that the TS Fuzzy PID control method has more excellent dynamic antistatic performances, as well as anti-jamming performance. The experiment shows that TS fuzzy PID control has the stronger adaptability robustness and transplant.

Simulation Analysis of Electro-Pneumatic Proportional Fuzzy-PID Control System Based on AMESim/Simulink

2014 ◽  
Vol 945-949 ◽  
pp. 2568-2572
Author(s):  
Si Yuan Wang ◽  
Guang Sheng Ren ◽  
Pan Nie
Keyword(s):  
Control System ◽  
Pid Control ◽  
Pid Controller ◽  
Simulation Analysis ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Proportional Control ◽  
Fuzzy Pid Controller ◽  
Design Requirements ◽  
Set Up

The test rig for hydro-pneumatic converter used in straddle type monorail vehicles was researched, and its electro-pneumatic proportional control system was set up and simulated based on AMESim/Simulink. Compared fuzzy-PID (Proportion Integral Derivative) controller with PID controller through fuzzy logic tool box in Simulink, the results indicate that, this electro-pneumatic proportional control system can meet design requirements better, and fuzzy-PID controller has higher accuracy and stability than PID controller.

The Application of Adaptive Fuzzy PID in the Liquid Level Cascade Control System

2013 ◽  
Vol 846-847 ◽  
pp. 321-324 ◽  
Author(s):  
Le Peng Song ◽  
Hua Bin Wang
Keyword(s):  
Control System ◽  
Pid Control ◽  
Cascade Control ◽  
Liquid Level ◽  
Water Tank ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Adaptive Fuzzy ◽  
Cascade Control System ◽  
Self Adaptive

As liquid level cascade system has the character the issue of non-linearity ,time variability and the overshoot,tradition PID control can not meet the requirement of precise molding system. So devise a self-_ adaptive fuzzy PID control .A self-_ adaptive fuzzy PID control combined PID to control calculate way and faintness to control the advantage of method, this text permits water tank to carry on mathematics model to design the double permit a water tank liquid misty PID string class control system. Matlab/Simulink and fuzzy logic toolbox are simulated to the single loop PID control system,the cascade control system and the cascade control system based on fuzzy self-tuning PID were simulated with Simulink. The analysis and simulation results indicate that the character issue of non-linearity ,time variability and the overshoot of the liquid level cascade control system based on a self-_ adaptive fuzzy PID controller are superior to previous of two methods.

Sign in / Sign up

Export Citation Format

Share Document