Intelligence Fusion Strategy of Forming Process Control for Sport Equipment in Rubber Products

2013 ◽  
Vol 440 ◽  
pp. 210-215
Author(s):  
Bo Bi ◽  
Lei Li
Keyword(s):  
Control Strategy ◽  
Pid Controller ◽  
Research Result ◽  
Chemical Properties ◽  
Control Effect ◽  
Forming Process ◽  
Sport Equipment ◽  
Control Precision ◽  
Physical Chemical ◽  
Complex Process

The physical-chemical properties of rubber products in sport equipment such as elasticity,tolerance,endurance,hardness etc not only are related to the factors of formulation in material and structure size etc, but also mainly depend on the control effect of forming process in vulcanizing phase. Aimed at the puzzle of being difficult to control resulted from uncertainty in vulcanizing phase, the paper proposed a sort of intelligence fusion control strategy. In this paper, it summed the control puzzle in complex vulcanizing phase, researched on the cybernetics characteristic, explored the control strategy of complex process with uncertainty, proposed a sort of intelligence fusion control strategy, and constructed the control model and algorithm. The simulation and engineering verification demonstrated that it could be stronger in robustness, and higher in control precision compared with PID controller. The research result shows that the proposed control strategy is feasible and effective.

Intelligence Based Control Strategy of Forming Process for Plastic & Rubber Products

2013 ◽  
Vol 345 ◽  
pp. 396-399
Author(s):  
Ping Tao ◽  
Qian Wu ◽  
Chao Xiao
Keyword(s):  
Control Strategy ◽  
Pid Controller ◽  
Control Algorithm ◽  
Simulation Experiment ◽  
Research Result ◽  
Chemical Properties ◽  
Control Effect ◽  
Forming Process ◽  
Control Precision ◽  
Complex Process

The physical-chemical properties of plastic & rubber products such as rigidity and endurance etc not only are related to the factors of formulations of materials & supplies and structure size etc, but also mainly depend on the control effect of forming process in the vulcanizing phase. Aimed at the puzzle of being difficult to control resulted from uncertainty in vulcanizing phase, the paper proposed a sort of intelligence based control strategy. In the paper, it summed the control puzzle in complex vulcanizing phase, explored the cybernetics characteristic, researched on control strategy of complex process with uncertainty, proposed a sort of intelligence based control strategy, and constructed the control algorithm. The simulation experiment and engineering verification demonstrated that it could be stronger in robustness, and higher in control precision compared with PID controller. The research result shows that it is feasible and effective to the proposed intelligence based control strategy.

A Sort of Fuzzy Intelligence Control Strategy for Complex System

2011 ◽  
Vol 187 ◽  
pp. 169-174 ◽  
Author(s):  
Yu Cheng Liu ◽  
Yu Bin Liu
Keyword(s):  
Complex System ◽  
Control Strategy ◽  
Effective Control ◽  
Control Effect ◽  
Expert Control ◽  
Control Precision ◽  
Optimal Pid Control ◽  
Intelligence Control ◽  
Fuzzy Control Algorithm ◽  
Better Than

For complex controlled object with the large time delay link, it was difficult to get effective control effect by means of traditional fuzzy control algorithm. Aimed at enhancing the control quality in control precision and so on for complex system, the paper proposed a sort of fuzzy intelligence control strategy. It fused the expert control experience combing with human simulated intelligence control, designed the control rule, proposed the mode of running controller and explored the principle of parameter calibrating layer. The system simulation experiment explained that the control effect was much better than optimal PID control in dynamic and steady quality. The results show that the fuzzy intelligent control strategy is reasonable and feasible, high in control precision, better in dynamical and steady control effect, and it represents very strong robustness.

An Improved PSO Algorithm of Optimizing Selection for Multi-Objective Controller Parameter

2013 ◽  
Vol 401-403 ◽  
pp. 1805-1808
Author(s):  
Yan Juan Ren
Keyword(s):  
Performance Index ◽  
Pid Controller ◽  
Research Result ◽  
Pso Algorithm ◽  
Performance Comparison ◽  
Control Effect ◽  
Global Optimal ◽  
Selection For ◽  
Selection Of ◽  
Improved Pso

For the same controlled process, different controller is radically different in control effect. Aimed at the puzzle of being difficult to select the controller for the incompatibility among control performance index, the paper proposed a sort of improved PSO algorithm. Based on the construction of objective function in multi-performance index parameter, the algorithm could quickly search and converge to control parameter in global optimal extremum corresponded to each controller and single out the controller through performance comparison excellently. In the paper, it took the controller selection of wastewater treatment system as an example, designed the algorithm of multi-modal HSIC controller of DO parameter, made the experiment of system simulation, and the simulation demonstrated that the HSIC controller could be stronger in robustness and better in dynamical and steady control quality compared with improved PID controller. The research result shows that it is reasonable and applicable to optimize selection of controller.

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.

Research on Control Strategy of Automatic Control System for Sewage Treatment

2013 ◽  
Vol 791-793 ◽  
pp. 690-693
Author(s):  
Zhang Hong ◽  
Xiao Liang Liu ◽  
Fang Wei
Keyword(s):  
Neural Network ◽  
Control Strategy ◽  
Bp Neural Network ◽  
Pid Control ◽  
Pid Controller ◽  
Treatment Process ◽  
Sewage Treatment ◽  
Bp Algorithm ◽  
Dissolved Oxygen Concentration ◽  
Control Effect

For the characteristics of the sewage treatment process and a combination of BP algorithm and conventional PID control, a PID controller is proposed based on BP neural network to realize the online adjustment of PID controller parameters. This control strategy will be applied to the control of the DO(Dissolved Oxygen) concentration in sewage treatment, and a contrast has been made with conventional PID control effect.

Based on the BP Neural Network-PID Series Control Boiler Main-Steam Temperature System Research

2011 ◽  
Vol 354-355 ◽  
pp. 968-973 ◽  
Author(s):  
Wen Zhu ◽  
Jian Ping Sun
Keyword(s):  
Neural Network ◽  
Control Strategy ◽  
Bp Neural Network ◽  
Pid Controller ◽  
Cascade Control ◽  
Steam Temperature ◽  
Control Effect ◽  
Real Time System ◽  
Main Steam ◽  
Neural Network Pid

Due to the boiler main-steam temperature system exists more serious characteristics,such as much capacitive,nonlinear,time-varying and lag, so adopt cascade control strategy. This paper design a control algorithm which is based on BP neural network, it can accelerate the regulating time, and combined with the conventional PID controller, constitute the BP neural network - PID cascade control strategy. This control strategy not only contain the BP neural network control in real time system strong anti-interference ability characteristic, but also fully utilize the PID controller response speed characteristic. The simulation results show that based on the BP neural network - PID series control boiler main-steam temperature system can achieve satisfactory control effect.

Garbage Incineration and Intelligent Fusion Strategy of Secondary Pollution Control

2013 ◽  
Vol 853 ◽  
pp. 323-328
Author(s):  
Yuan Min Ni ◽  
Lei Li
Keyword(s):  
Control Strategy ◽  
Pollution Control ◽  
Control Algorithm ◽  
Digital Simulation ◽  
Combustion Process ◽  
Optimal Controller ◽  
Control Effect ◽  
Control Precision ◽  
Secondary Pollution ◽  
And Control

To control the secondary atmosphere pollution produced by exhaust gas in process of garbage incineration, the paper presented a sort of intelligence fusion control strategy in city garbage incineration. In the paper, aimed at the running properties of garbage incinerator and combined the mechanism of garbage combustion and contamination generation, it studied the characteristic of controlled combustion process, proposed a sort of fusion control strategy based on human simulated intelligence for controlled process, constructed the corresponding control algorithm. Finally it took a two order model of combustion process with large lag as an example that is very nearly similar to controlled process characteristic of garbage incineration, and made the contrast experiment of digital simulation respectively by the Smith optimal controller and the presented fusion control algorithm by means of the platform of MATLAB. The response curve of simulation shows that the fusion control algorithm is better than by Smith optimal controller in control effect of anti-jamming performance and control index obviously. The experiment results show that the proposed fusion control strategy is reasonable, feasible and effective for secondary pollution control, and it is high in control precision, better in dynamical and steady quality, and very strong in robustness.

Chlorinated Organics in Nearshore Waters and Tributaries of the St. Clair River

1986 ◽  
Vol 21 (3) ◽  
pp. 344-350 ◽  
Author(s):  
Barry G. Oliver ◽  
Klaus L.E. Kaiser
Keyword(s):  
United States ◽  
Suspended Sediment ◽  
Waste Disposal ◽  
Large Volume ◽  
Water Samples ◽  
Chemical Properties ◽  
Low Level ◽  
Chemical Company ◽  
Physical Chemical ◽  
The Individual

Abstract The concent rat ions of hexachloroethane (HCE), hexachlorobutadiene (HCBD), pentachlorobenzene (QCB), hexachlorobenzene (HCB) and octachlorostyrene (OCS) in large volume water samples show that the major sources of these chemicals to the St. Clair River are Dow Chemical Company effluents and, to a lesser degree, Sarnia’s Township ditch which drains one of Dow’s waste disposal sites. Tributaries entering the river on both sides of the Canada/United States border contain measurable concentrations of these chemicals indicating low level contamination throughout the area. The degree of water/suspended sediment partitioning of the chemicals (Kp) was studied. Kp values for the individual chemicals changed in a manner consistent with changes in their physical-chemical properties.

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