In order to efficiently and accurately adjust the shearer traction speed, a novel approach based on Takagi-Sugeno (T-S) cloud inference network (CIN) and improved particle swarm optimization (IPSO) is proposed. The T-S CIN is built through the combination of cloud model and T-S fuzzy neural network. Moreover, the IPSO algorithm employs parameter automation adjustment strategy and velocity resetting to significantly improve the performance of basic PSO algorithm in global search and fine-tuning of the solutions, and the flowchart of proposed approach is designed. Furthermore, some simulation examples are carried out and comparison results indicate that the proposed method is feasible, efficient, and is outperforming others. Finally, an industrial application example of coal mining face is demonstrated to specify the effect of proposed system.
Roller crusher is widely used in solid and block material pulverizing. Roll gap between the rollers is usually adjusted to satisfy the particle size of output material. In order to realize convenient adjustment, a roll gap control scheme based on electro-hydraulic technology is designed and optimized. And Fuzzy-PID is applied to realize the automatic process. Moreover, decision factor self-correction is introduced to balance the number of Fuzzy rules and system precision. Finally, an experiment platform and some simulations are conducted to validate the performance of the proposed approach.
Roll gap between the two rollers of crusher is adjusted constantly to satisfy the particle size of output material. In order to realize convenient adjustment, a roll gap control scheme based on hydraulic technology is designed and optimized in this paper. And an adaptive reference model is applied to compensate synchronous error of the rollers. Then simulation model and algorithm structure are elaborated subsequently. Finally, an experiment platform is built to validate the performance of the proposed approach.
Abstract:Hydraulic buffer systems play a significant role in energy absorption and improving belt arrest reliability in downward belt conveyors. In order give hydraulic buffer systems more preferable buffer properties, a parameters optimization method based on a reference model is proposed. Firstly, the working principle of a hydraulic buffer system for a belt arrestor is provided. Secondly, the mathematical model of the system is built and a reference model of buffer chamber pressure is constructed utilizing a second-order system. Furthermore, a genetic algorithm is introduced to optimize the system parameters. Finally, some simulation examples are carried out on the Simulink software. The simulation results show that the pressure peak in buffer process can drop down and that pressure fluctuation in buffer end processes decrease substantially after optimization. The parameters optimization method for hydraulic buffer systems is applicable to different structure parameters of the buffer cylinder.
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