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英语翻译
We also compared our results with a classical PID controller and with a fuzzy Mamdani controller,to measure how much the adaptive fuzzy approach could improve the performance.Of course,our fuzzy con- troller (designed with ANFIS) was better in tracking and adaptability than the other controllers.
Another advantage of this method over classical quantitative controllers is that it does not require a fixed sampling time.Therefore,the proposed design confirms the fact that fuzzy control is relevant to the control fast of non-linear processes such as stepping motor drives where quantitative methods are not al- ways appropriate.
In this paper,the feasibility of fuzzy control for step- ping motor drives has been proved and illustrated by simulation and experimentation.The best parameters for the fuzzy controller were determined by using the ANFIS methodology and also by using simulations of the stepping motor dynamics.An experimental system was used to validate experimentally the tracking ability and the insensibility to plant parameter changes.The fuzzy controller presented very interesting tracking features and was able to respond to different dynamic conditions.Also,the fuzzy control computation is very inexpensive,and this regulator could be used for the control of machine tools and robotics manipulators [6] without significantly increasing the cost of the drive.The only extra cost is for the optical encoder.Another advantage of this method over classical quantitative controllers is that it does not require a fixed sampling time.Therefore,the proposed design confirms the fact that fuzzy control is relevant to the control fast of non-linear processes such as step- ping motor drives where quantitative methods are not
always appropriate.
We would like to thank the Research Grant Com- mittee of COSNET and CONACYT for the financial support for performing this research work.We would also like to thank the Department of Computer Sci- ence of Tijuana Institute of Technology for the time and resources given to this project.
We also compared our results with a classical PID controller and with a fuzzy Mamdani controller,to measure how much the adaptive fuzzy approach could improve the performance.Of course,our fuzzy con- troller (designed with ANFIS) was better in tracking and adaptability than the other controllers.
Another advantage of this method over classical quantitative controllers is that it does not require a fixed sampling time.Therefore,the proposed design confirms the fact that fuzzy control is relevant to the control fast of non-linear processes such as stepping motor drives where quantitative methods are not al- ways appropriate.
In this paper,the feasibility of fuzzy control for step- ping motor drives has been proved and illustrated by simulation and experimentation.The best parameters for the fuzzy controller were determined by using the ANFIS methodology and also by using simulations of the stepping motor dynamics.An experimental system was used to validate experimentally the tracking ability and the insensibility to plant parameter changes.The fuzzy controller presented very interesting tracking features and was able to respond to different dynamic conditions.Also,the fuzzy control computation is very inexpensive,and this regulator could be used for the control of machine tools and robotics manipulators [6] without significantly increasing the cost of the drive.The only extra cost is for the optical encoder.Another advantage of this method over classical quantitative controllers is that it does not require a fixed sampling time.Therefore,the proposed design confirms the fact that fuzzy control is relevant to the control fast of non-linear processes such as step- ping motor drives where quantitative methods are not
always appropriate.
We would like to thank the Research Grant Com- mittee of COSNET and CONACYT for the financial support for performing this research work.We would also like to thank the Department of Computer Sci- ence of Tijuana Institute of Technology for the time and resources given to this project.
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