Research on Tyred Machinery Chassis Dynamometer

2013 ◽  
Vol 631-632 ◽  
pp. 1106-1110
Author(s):  
Wei Zhao ◽  
Qiang Wang ◽  
Sheng Li Song
Keyword(s):  
Control System ◽  
System Performance ◽  
Pid Controller ◽  
Fuzzy Pid ◽  
Chassis Dynamometer ◽  
Technical Parameters ◽  
The Road ◽  
Fuzzy Pid Controller ◽  
System A ◽  
Line Measure

In the tyred machinery chassis dynamometer control system, a fuzzy PID controller was used to adjust the exciting current of a DC dynamometer in order to change the resistance load torque, so the requirement of roller load for simulating the run resistance from the road surface was satisfied. A fuzzy PID arithmetic was designed to control the resistance loads, the system performance was improved by simulation. The software of the detection line measure-control system was designed in VB, the technical parameters of the machinery chassis could the automatically detected.

Study of Vice-Steering Control System for Training Car

2011 ◽  
Vol 142 ◽  
pp. 79-82
Author(s):  
Wei Chun Zhang ◽  
Bing Bing Ma ◽  
Xian Bin Du ◽  
Bao Hao Pei ◽  
Jie Chen
Keyword(s):  
Mathematical Model ◽  
Fuzzy Logic ◽  
Control System ◽  
Dynamic Characteristics ◽  
Pid Controller ◽  
Fuzzy Controller ◽  
Fuzzy Pid ◽  
Steering Control ◽  
Fuzzy Pid Controller ◽  
System A

Based on analyzing the structure and dynamic characteristics of this system, a dynamical mathematical model is established. To overcome the problems when using fuzzy controller or PID controller respectively and increase precision, a P-fuzzy-PID mode controller and a fuzzy PID controller is designed to control the system. The module of simulink which is a part of MATLAB is used to construct a monolithic mould. The fuzzy logic toolbox is used to construct a fuzzy mould. The results of simulation show that the performance of control becomes better by using this design.

The Sinter Mixture Moisture Control System Based on Fuzzy PID Controller

2013 ◽  
Vol 457-458 ◽  
pp. 899-904
Author(s):  
Ting Gui Li ◽  
Qin Hui Gong
Keyword(s):  
Control System ◽  
System Performance ◽  
Pid Controller ◽  
Production Condition ◽  
Structural Features ◽  
Fuzzy Pid ◽  
Moisture Control ◽  
Fuzzy Pid Controller ◽  
Self Tuning ◽  
Sinter Mixture

Because the sinter mixture moisture control system has time-varying, nonlinear and time-delay characteristics, it is difficult to establish its precise mathematical model. According to the defects that the conventional PID control in the fixed parameter is difficult to guarantee the system performance, this paper proposed the parameter self-tuning fuzzy PID controller which is used to the system. Based on the sintering furnace structural features and control performance requirements, the PID parameters are set by fuzzy logic reasoning. The actual operation results proved that the parameter self-tuning fuzzy PID controller improved more obviously the system performance than the original PID controller, and stabilized the sinter mixture moisture, and improved the sintering production condition and promoted the production capacity.

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.

Design and Implementation of Fuzzy PID Controller for Brushless DC Motor Control System

2013 ◽  
Vol 432 ◽  
pp. 472-477
Author(s):  
Wei Fan ◽  
Tao Chen
Keyword(s):  
Control System ◽  
Digital Signal Processor ◽  
Pid Controller ◽  
Fuzzy Controller ◽  
Digital Signal ◽  
Dc Motor ◽  
Brushless Dc Motor ◽  
Fuzzy Pid ◽  
Brushless Dc ◽  
Fuzzy Pid Controller

This paper presents a robust fuzzy proportional-integral-derivative (PID) controller for brushless DC motor (BLDCM) control system. The hardware circuit of the BLDCM control system is designed and implemented using a digital signal processor (DSP) TMS320LF2407A and a monolithic BLDCM controller MC33035 as the core. Furthermore, a fuzzy PID controller, which combines the advantages of good robustness of fuzzy controller and high precision of conventional PID controller, is employed in the hardware system, thereby yielding a digital, intelligent BLDCM control system. Experimental results have shown that the control system can run steadily and control accurately, and have convincingly demonstrated the usefulness of the proposed fuzzy PID controller in BLDCM control system.

Study on Control Strategies of Semi-Active Air Suspension for Heavy Vehicles Based on Road-Friendliness

2012 ◽  
Vol 452-453 ◽  
pp. 328-333
Author(s):  
Feng He ◽  
Jing Zhao ◽  
Hao Yu Wang
Keyword(s):  
Pid Controller ◽  
Fuzzy Controller ◽  
Control Strategies ◽  
Fuzzy Pid ◽  
Control Effect ◽  
The Road ◽  
Fuzzy Pid Controller ◽  
Air Suspension ◽  
Road Excitation ◽  
Band Limited

Targeting the road-friendliness of vehicles, the paper has analyzed dynamic deformation and dynamic load of tires under different control strategies through co-simulation. A vehicle dynamics model with semi-active air suspension has been made through using Adams, and a PID controller, a fuzzy controller and a fuzzy PID controller have been set in the Matlab to adjust the damping of the suspension, with the road excitation modeled through band-limited white noise. The result shows that the fuzzy PID controller has overcome the shortcomings of the PID controller and the fuzzy controller and a better control effect has been achieved.

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