Fuzzy-Adaptive PID Based Tow Tension Controller for Robotic Automated Fiber Placement

2014 ◽  
Vol 643 ◽  
pp. 48-53 ◽  
Author(s):  
Jie Chen ◽  
Wen Jun Xu ◽  
Ben Wang ◽  
Yu Gang Duan ◽  
Xiao Hui Zhang
Keyword(s):  
Fuzzy Logic ◽  
Steady State ◽  
Working Conditions ◽  
Pid Control ◽  
Composite Structures ◽  
Cost Effective ◽  
Fiber Placement ◽  
Automated Fiber Placement ◽  
Adaptive Pid Control ◽  
Fuzzy Adaptive

Robotic automated fiber placement (Robotic AFP) was a cost-effective and highly innovative approach to produce large and complex composite structures. In order to achieve desired qualities, the tow tension of the process required to becontrolled accurately. Due to the high nonlinearity of the system, such as the large elastic modulus, flexibility and viscosity of the tow, traditional methods failed to work effectively. A fuzzy-adaptive PIDcontroller combining fuzzy logic and adaptive PID together was proposed in this work. Fuzzy logic was able to respond quickly to disturbances without the need for an accurate model and adaptive PID control could eliminate the steady-state error by adapting its parameters to the working conditions. With this method, the tow tension could be precisely regulated thus improved the qualities of the composite structures.

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.

Study of integral hat-stiffened composite structures manufactured by automated fiber placement and co-curing process

2020 ◽  
Vol 246 ◽  
pp. 112427
Author(s):  
Cong Zhao ◽  
Xianfeng Wang ◽  
Xingyu Liu ◽  
Cheng Ma ◽  
Qiyi Chu ◽  
...  
Keyword(s):  
Composite Structures ◽  
Curing Process ◽  
Fiber Placement ◽  
Automated Fiber Placement

Corrigendum to “Effect of automated fiber placement (AFP) manufacturing signature on mechanical performance of composite structures” [Compos. Struct. 228 (2019) 111335]

2020 ◽  
Vol 233 ◽  
pp. 111700
Author(s):  
Minh Hoang Nguyen ◽  
Avinkrishnan A. Vijayachandran ◽  
Paul Davidson ◽  
Damon Call ◽  
Dongyeon Lee ◽  
...  
Keyword(s):  
Composite Structures ◽  
Mechanical Performance ◽  
Fiber Placement ◽  
Automated Fiber Placement

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.

Stability Control and Simulation of Wheel-Legged Mobile Robot in Mechanical Engineering

2013 ◽  
Vol 644 ◽  
pp. 123-128
Author(s):  
Ling Yu Sun ◽  
Jian Hua Zhang ◽  
Xiao Jun Zhang
Keyword(s):  
Mobile Robot ◽  
Pid Control ◽  
Control Method ◽  
Three Dimensional ◽  
Stability Domain ◽  
Stability Control ◽  
Terrestrial Environment ◽  
The Stability ◽  
Adaptive Pid Control ◽  
Fuzzy Adaptive

The wheel-legged mobile robot in a complex three-dimensional environment has strong through capacity .Study is very critical for the stability of the control of their body systems. In this paper , based on analysis of the structure of wheel-legged mobile robot designed, the stability is evaluated by the use of (Effective Mass Center) EMC , and the stability domain is established accordingly. A fuzzy adaptive PID control method is created , and verified by ADAMS and MATLAB co-simulation . Simulation results show that the robot in different terrestrial environment, can maintain good stability.

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