The Computation of Desired Ball Velocity after Striking Based on Self-tunning Fuzzy Algorithm for Robotic Table Tennis

Su, Hu; Xu, Donghao; Huang, Yan-Long; Tan, Min

doi:10.3724/sp.j.1004.2012.00923

Cited by 2 publications

(2 citation statements)

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“…The control problem of the nonlinear MIMO (multi-input multioutput) system is a key point in research difficulties. [1][2][3][4][5][6][7] During industrial production, the factors that affect the temperature change during the fermentation process include fermentation heat from the vegetable waste, mechanical heat caused by the motor-stirring, heat conduction from the heating devices, and the heat loss of the fermentation reactor shell. All these factors should be considered when adjusting the temperature of the fermentation reactor.…”

Section: Introductionmentioning

confidence: 99%

“…This approach promotes the development of those nonlinear MIMO systems. [3][4][5][6][7] Although the T-S model of fuzzy control can design the MIMO systems, there is still a large gap between its theoretical research and practical applications. In practice, the design of a multivariable fuzzy controller involves converting the multivariable problem into a problem requiring the control of many single variables, respectively, which reduces precision.…”

Section: Introductionmentioning

confidence: 99%

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Design for vegetable waste fermentation control systems based on semi-tensor product fuzzy controller

Wang

Guo

2018

Advances in Mechanical Engineering

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A multivariable fuzzy controller was designed to solve the control problem of vegetable waste fermentation. The knowledge-based fuzzy reasoning was constructed according to the sample data from both the fermentation process and the rule of temperature change in the control process. It is represented using the mathematical method of semitensor product matrices. The structural matrix of the fuzzy logic was constructed and the complex fuzzy reasoning was converted into simple matrix operations. In addition, a new algorithm based on the least in-degree method is put forward, solving the problem of control rules being incomplete and inconsistent. It was used for the design of the fuzzy controller on vegetable waste fermentation. The result of experiment proved that this control method is effective; the control method improves the adjustment speed as well as the control precision.

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