Tuning of PID Parameters and Fuzzy Adaptive PID Control of the Hydrostatic Driving System

2011 ◽  
Vol 403-408 ◽  
pp. 5112-5116 ◽  
Author(s):  
Chang Gao Xia ◽  
Chong Cao
Keyword(s):  
Input Signal ◽  
Pid Control ◽  
Pid Controller ◽  
Optimization Method ◽  
Motor Speed ◽  
Driving System ◽  
Displacement Pump ◽  
Adaptive Ability ◽  
Adaptive Pid Control ◽  
Fuzzy Adaptive

Composed of a variable displacement pump and a constant displacement motor, the hydrostatic driving system is a kind of closed speed control system with adjustable displacement. It is widely used in the field of engineering vehicle and other fields. Based on an analysis of the constitution and mathematical model of the hydrostatic driving system, the present study tuned PID parameters by using the critical proportioning method and the optimization method of NCD respectively. Then a kind of fuzzy adaptive PID controller was designed on the basis of the traditional PID control and the fuzzy control theory. In the controller, fuzzy logic was used to realize online self-tuning of PID parameters according to the motor speed error and its derivative, so that the system could have better adaptive ability and strong disturbance resisting performance. The dynamic simulation was made in MATLAB/SIMULINK. The simulation results show that the optimization method of NCD has better tuning effect and the response performance of the fuzzy adaptive PID controller is better than that of the classic one. Besides, it should be noted that a drawback was found about the fuzzy adaptive PID control. On the basis of fixed scale factors, a group of quantification factors is appropriate for a specific input signal, but for other signals, the response of the system is not so ideal. A method of adjusting quantification factors according to input signal was adopted to solve the above problem. Automatic adjusting of quantification factors was realized, and this could ensure ideal response to all input signals.

Research on Control Method of a Novel Type of Excavator Based on Multi Degree-Of-Freedom Controllable Mechanism

2011 ◽  
Vol 201-203 ◽  
pp. 1949-1954 ◽  
Author(s):  
Gan Wei Cai ◽  
Du Chao Wu ◽  
Yu Chen Pan ◽  
Xi Yong Xu ◽  
Zhuan Zhang
Keyword(s):  
Pid Control ◽  
Pid Controller ◽  
Control Method ◽  
Mimo System ◽  
Degree Of Freedom ◽  
New Type ◽  
Actual Response ◽  
Adaptive Pid Control ◽  
Logic Inference ◽  
Fuzzy Adaptive

The new type of excavator based on multi degree-of-freedom controllable mechanism is a typical nonlinear multi-input-multi-output (MIMO) system, of which the closed chain constraints make it with strong coupling relationships. Consequently, the classic PID control method is not able to satisfy the control demands of the system. This paper introduces a fuzzy adaptive PID control method focusing on the improvement of the control accuracy of the excavator based on fuzzy logic inference according to the actual response of the control system, aiming at the automatically online adjusting of the PID parameters. A simulation study is also proposed. The correctness and validity of the project is verified by comparing the simulation results of the fuzzy adaptive PID controller with those of the classic PID controller. Results show that the former one designed for the new mechanical excavator has shorter settling time, and with less overshoot, than the latter one.

scholarly journals Research on speed control of high-speed train based on multi-point model

2019 ◽  
Vol 50 (2) ◽  
pp. 35-46 ◽  
Author(s):  
Tao Hou ◽  
Yang-yang Guo ◽  
Hong-xia Niu
Keyword(s):  
Pid Control ◽  
Pid Controller ◽  
High Speed ◽  
Speed Control ◽  
Fast Response ◽  
High Speed Train ◽  
Point Model ◽  
Train Speed ◽  
Adaptive Pid Control ◽  
Fuzzy Adaptive

The traditional train speed control research regards the train as a particle, ignoring the length of the train and the interaction force between carriages. Although this method is simple, the control error is large for high-speed trains with the characteristics of power dispersion. Moreover, in the control process, if the length of the train is not considered, when the train passes the slope point or the curvature point, the speed will jump due to the change of the line, causing a large control error and reducing comfort. In order to improve the accuracy of high-speed train speed control and solve the problem of speed jump when the train runs through variable slope and curvature, the paper takes CRH3 EMU data as an example to establish the corresponding multi-point train dynamics model. In the control method, the speed control of high-speed train needs to meet the fast requirement. Comparing the merits and demerits of classical PID control, fuzzy control and fuzzy adaptive PID control in tracking the ideal running curve of high-speed train, this paper chooses the fuzzy adaptive PID control with fast response. Considering that predictive control can predict future output, a predictive fuzzy adaptive PID controller is designed, which is suitable for high-speed train model based on multi-point. The simulation results show that the multi-point model of the high-speed train can solve the speed jump problem of the train when passing through the special lines, and the predictive fuzzy adaptive PID controller can control the speed of the train with multi-point model, so that the train can run at the desired speed, meeting the requirements of fast response and high control accuracy.

Straight-Move Robot Control System with LabView-Based Proportional Integral Derivative (PID) Control

2019 ◽  
Vol 3 (2) ◽  
pp. 13-24
Author(s):  
Andrean George W
Keyword(s):  
Pid Control ◽  
Rotational Speed ◽  
Pid Controller ◽  
Dc Motor ◽  
Motor Speed ◽  
Labview Software ◽  
Dc Motors ◽  
Dc Motor Control ◽  
Process System ◽  
Interface Devices

Abstract - Control and monitoring of the rotational speed of a wheel (DC motor) in a process system is very important role in the implementation of the industry. PWM control and monitoring for wheel rotational speed on a pair of DC motors uses computer interface devices where in the industry this is needed to facilitate operators in controlling and monitoring motor speed. In order to obtain the best controller, tuning the Integral Derifative (PID) controller parameter is done. In this tuning we can know the value of proportional gain (Kp), integral time (Ti) and derivative time (Td). The PID controller will give action to the DC motor control based on the error obtained, the desired DC motor rotation value is called the set point. LabVIEW software is used as a PE monitor, motor speed control. Keyword : LabView, Motor DC, Arduino, LabView, PID.

Pressing speed stability control of a special ceramic roller bearing press based on fuzzy adaptive PID

2021 ◽  
pp. 1-16
Author(s):  
Lijie Yang ◽  
Guimei Wang ◽  
Huadong Zhang ◽  
Jiehui Liu ◽  
Yachun Zhang
Keyword(s):  
Pid Control ◽  
Simulation Analysis ◽  
Roller Bearing ◽  
Speed Control ◽  
Stability Control ◽  
Interference Signal ◽  
Ceramic Roller ◽  
Speed Stability ◽  
Adaptive Pid Control ◽  
Fuzzy Adaptive

A special ceramic roller bearing press (SCRBP) is developed to press two bearings efficiently and precisely at the same time. A speed control mathematical model of the bearing press is built to obtain stability bearing pressing speed. The fuzzy adaptive PID controller of the bearing pressing speed of SCRBP is designed. The simulation model is also built. Fuzzy adaptive PID control is compared with conventional PID control. By simulation analysis, the simulation results show that adjusting time of fuzzy adaptive PID control is short, and its overshoot is very small, almost coincides with the set pressing speed. Moreover, fuzzy adaptive PID is suitable for the pressing speed control of the bearing pressing speed system with step interference signal. The pressing stability speed is obtained by fuzzy adaptive PID control.

Simulation Research on Fuzzy Adaptive PID Control of Variable Pump Control System

2012 ◽  
Vol 220-223 ◽  
pp. 880-883
Author(s):  
Hui Wang ◽  
Zhuo Xu
Keyword(s):  
Pid Control ◽  
Pid Controller ◽  
Fuzzy Controller ◽  
Response Speed ◽  
System Response ◽  
Fuzzy Pid Control ◽  
Simulation Research ◽  
Output Pressure ◽  
System Output ◽  
Fuzzy Adaptive

According to the problem of large overshoot in the variable pump constant pressure output, the fuzzy controller and PID controller were combined. The dynamic response of system output pressure was obtained by combining simulation with a fuzzy adaptive PID controller designed in Matlab/Simulink and mechanical hydraulic model established in AMESim. The simulation results show that fuzzy PID control can achieve the goal of system response without overshoot, and response speed is improved further. The anti-interference ability is also stronger.

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