Analysis and simulation research on thickness control effect of U-groove aluminum alloy profile based on ECAP with rubber mandrel

2022 ◽  
Author(s):  
Hong-yu Wang ◽  
Ji-rui Li ◽  
Sheng-nan Shi ◽  
Jun-cai Sun ◽  
Jie Sun ◽  
...  
Keyword(s):  
Aluminum Alloy ◽  
Control Effect ◽  
Simulation Research ◽  
Thickness Control

Numerical Simulation Research on Springback Controlling Methods of Aluminum Alloy Panel during Hydroforming

2016 ◽  
Vol 851 ◽  
pp. 163-167
Author(s):  
Dong Yan Lin ◽  
Yi Li
Keyword(s):  
Numerical Simulation ◽  
Aluminum Alloy ◽  
Process Parameters ◽  
Orthogonal Experiment ◽  
Blank Holder Force ◽  
Scoring Method ◽  
Simulation Research ◽  
Blank Holder ◽  
Hydroforming Process

The hydroforming process of the aluminum alloy panel was simulated by the software DYNAFORM. The effects of process parameters (blank holder force, depth of panel and height of draw bead) on springback of the aluminum alloy were investigated. The max springback of the panel was analyzed by weighted scoring method. Then the process parameters were synthetically optimized for the max positive and negative springback. The results showed that the height of draw bead affects obviously the comprehensive springback of the panel. The optimization of the process parameters obtained by the orthogonal experiment can effectively reduce the max springback of the panel.

Temperature Control System Based on Electronic Boiler

2013 ◽  
Vol 325-326 ◽  
pp. 1197-1201
Author(s):  
Guo Sheng Xu
Keyword(s):  
Control System ◽  
Fuzzy Control ◽  
Temperature Control ◽  
Fuzzy Controller ◽  
System Simulation ◽  
Temperature Control System ◽  
Control Effect ◽  
Simulation Research ◽  
Control Regulation ◽  
Control Scheme

Research has been done aimed at the boiler's temperature control system, and available control scheme is put forward. Combining with the output response of control system, simulation research and the control regulation of fuzzy controller are done to analyse, after experiments for many times repeatedly, fuzzy control regulation is ensured. The simulation result indicates that control effect is ideal, which means this scheme is identified as ideal temperature control system scheme.

Non-Linearization Simulation Research of Linear Active Disturbance Rejection Controller

2013 ◽  
Vol 427-429 ◽  
pp. 1263-1267
Author(s):  
En Rang Zheng ◽  
Hao Yang ◽  
Shi Chen Wang
Keyword(s):  
Disturbance Rejection ◽  
Pid Controller ◽  
Simulation Experiment ◽  
Nonlinear Controller ◽  
Control Effect ◽  
Simulation Research ◽  
Active Disturbance Rejection ◽  
Linear And Nonlinear ◽  
And Performance ◽  
Better Than

The characteristics of PID controller, Active Disturbance Rejection Controller (ADRC) and Linear Active Disturbance Rejection Controller (LADRC) are introduced in the paper, then the parts which can be improved are analyzed, which leads to the topic of balancing linear and nonlinear elements in controller. LADRC with FFTD is used as an example in simulation experiment operated in Matlab7.0.The results shows that the control effect of LADRC with FFTD is better than other three controllers above. The simulation results and perspectives in paper offers reference for combining linear and nonlinear controller and balancing difficulty and performance.

Research on Single Neuron Adaptive PID Controller

2014 ◽  
Vol 651-653 ◽  
pp. 826-830 ◽  
Author(s):  
Xiu Jia Chen ◽  
Hong Di Qiu
Keyword(s):  
Pid Controller ◽  
Single Neuron ◽  
Control Effect ◽  
External Disturbances ◽  
Simulation Research ◽  
Process System ◽  
Self Tuning ◽  
The Stability ◽  
Actual Control ◽  
Controlled Object

The paper focuses on single neuron adaptive PID controller based on unsupervised Hebb algorithm, and simulation research on the controller is carried out for a second-order pure lag process system. Simulation results show that through learning and adjusting weights of single neuron adaptive PID controller, its online self-tuning ability can make timely adjustment of PID controller parameters according to controlled object changes and external disturbances in order to ensure that the stability and robustness of the system and, ultimately, more satisfactory actual control effect is obtained. At last, the control characteristics and parameter design rules are concluded.

Simulation Research on Load-Imitating Test Equipment for Hydraulic Drive Unit of a Quadruped Robot Based on Feed-Forward Decoupling Control

2013 ◽  
Vol 365-366 ◽  
pp. 839-846 ◽  
Author(s):  
Ling Xiao Quan ◽  
De Zhi Tian ◽  
Bin Yu
Keyword(s):  
Hydraulic Drive ◽  
Decoupling Control ◽  
Test Equipment ◽  
Load Force ◽  
Control Effect ◽  
Drive Unit ◽  
Simulation Research ◽  
Force System ◽  
Feed Forward ◽  
Hydraulic Drive Unit

This paper establishes the simulation model of a load-imitating test equipment for a hydraulic drive unit of a quadruped bionic robot, analyzing load force changes during the work process of the hydraulic drive unit, and researching load-imitating characteristics. A Strategy based on feed-forward decoupling control is proposed to realize the decoupling between the position system and the force system of the load-imitating test equipment to improve load-imitating precision. The results show that control effect of feed-forward decoupling control is satisfactory, and this control strategy can effectively improve load-imitating precision of the test equipment. The research above can also provide theoretical foundation for test application of the hydraulic drive unit.

The Application of PID Based on Optimized RBF in Thickness Control of Strip Steel

2012 ◽  
Vol 466-467 ◽  
pp. 52-56
Author(s):  
Yu Zhen Yu ◽  
Xin Yi Ren ◽  
Chun Yan Deng ◽  
Xiao Hui Wang
Keyword(s):  
Neural Network ◽  
Control System ◽  
Control Strategy ◽  
Pid Controller ◽  
Control Method ◽  
Rbf Neural Network ◽  
Pso Algorithm ◽  
Strip Thickness ◽  
Control Effect ◽  
Thickness Control

The strip thickness control system is difficult to establish an accurate mathematical model, and traditional PID control strategy has a poor adaptive ability, so the effect of control is always not satisfying. According to the problems above, a new control strategy of self-tuning PID controller based on RBF neural network whose parameters are optimized by PSO algorithm is proposed in the paper. The control method integrates advantages of RBF neural network as well as PID controller and good global search capability of PSO algorithm. The simulation results indicate that the method not only improves control performance and dynamic quality, but also has strong self-adapting ability and robustness. It achieved a very good control effect when used in strip thickness control system that proved the correctness and effectiveness of the control method.

Simulation Research of Fuzzy Controller with Sigmoid Scaling Factor

2013 ◽  
Vol 846-847 ◽  
pp. 264-267
Author(s):  
Hui Fang Wang ◽  
Xiao Ming Liang ◽  
Zi Yu Liu
Keyword(s):  
Membership Function ◽  
Performance Optimization ◽  
Fuzzy Controller ◽  
Dynamic Performance ◽  
Scaling Factor ◽  
The Other ◽  
Sigmoid Function ◽  
Control Effect ◽  
Simulation Research ◽  
Control Rules

For the fuzzy controller performance optimization, several optimization strategies on the membership function, control rules and scaling factors respectively are analyzed and compared, on the basis, the sigmoid function is introduced to replace the linear factor so to optimize the conventional fuzzy controller. The theoretical analysis is carried from mapping relations of sigmoid scaling factor and relations between it and the other parameters. It is shown that sigmoid scaling factor can get the same control effect to adjusting control rules or membership function. It can ensure the dynamic performance and at the same time effectively reduce the steady-state error, but the adjusting parameter is far less than the other strategies, it is easy and feasible.

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