Research On Fuzzy Integral And Control And Its Application In Pipeline Robot Of Remove The Weld Beading

As a new subject,fuzzy mathematics develops rapidly,and its application is widely used in many fields,such as cluster analysis,system evaluation,automatic control,social science and so on.In this paper,aiming at the engineering problem of the pipeline robot of remove the weld beading,the fuzzy measure and integral are studied,and the fuzzy controller is designed,the specific research content is as follows:1.This paper further researches on fuzzy measures and integrals,and a concept of non-additive measure is given.?-fuzzy quasi-product operator and ?-fuzzy quasi-sum operator with adjustable parameters for specific practical problems are designed.Based on this non-additive measure and ?-fuzzy quasi-product operator,the definition of fuzzy quasi-product probability integral is given,and the theorems satisfying the fuzzy quasi-product are proved.2.The performance status of pipeline robot of remove the weld beading affects its work efficiency.In order to solve this problem,a new fuzzy evaluation method using fuzzy quasi-product probability integral is proposed in this paper to evaluate the performance state of the pipeline robot.Compared with the traditional fuzzy comprehensive evaluation method,the validity and rationality of the method are verified.This method overcomes the fuzziness of weight value in fuzzy comprehensive evaluation.3.In view of the hot problem of fuzzy controller,considering that the traditional fuzzy controller will be affected by small random quantities in the actual control,a random variant domain fuzzy controller is designed.A random variant domain telescopic factor is designed,and its rationality is verified.It is combined with the fuzzy controller,which is applied to the control problem of the stability of the fixture mechanism of the pipeline robot,and the manual control is upgraded to the random variant domain fuzzy controller for control,which improves the control accuracy.The simulation experiment compares it with the traditional fuzzy controller,and the research finds that the response speed has improved significantly.