Proceedings of the 3rd World Congress on Intelligent Control and Automation (Cat. No.00EX393)
DOI: 10.1109/wcica.2000.862726
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The research on fuzzy control for performance improvement

Abstract: The vocational technology education cenfre of Psnzhihua iron and steel (group) Corporation panzhihua 6 I7000 Abstract: Several methods on b y control for perfimprovement anz introduced in this paper, tben their specialities and situations of application are summarized

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Cited by 4 publications
(4 citation statements)
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“…The control flow graph is expressed in Fig 2. 2 The fuzzy control model [6] According to experience, the domain is chosen as flowing: The domain of yaw rate E is chosen as {-6 6}, the domain of yaw rate EC is chosen as {-10 10}, and the domain of rear turning angle U is chosen as {-3 3}. The membership function curve of input and output is expressed in The input variable should be transferred from basic domain to domain of fuzzy sets.…”
Section: The Controller Model 21 the Introduction Of The Control Methodsmentioning
confidence: 99%
“…The control flow graph is expressed in Fig 2. 2 The fuzzy control model [6] According to experience, the domain is chosen as flowing: The domain of yaw rate E is chosen as {-6 6}, the domain of yaw rate EC is chosen as {-10 10}, and the domain of rear turning angle U is chosen as {-3 3}. The membership function curve of input and output is expressed in The input variable should be transferred from basic domain to domain of fuzzy sets.…”
Section: The Controller Model 21 the Introduction Of The Control Methodsmentioning
confidence: 99%
“…Reference to single neuron PSD control algorithm [9], a self-learning PI controller was designed based on the characteristic of PMA. Shown in Fig.3, the controller was composed of a PI controller and a self-learning controller; the former can predict and compensate the displacement bias and the latter adjust the initial PWM ratio and the proportion coefficient.…”
Section: The Algorithm In Motion Stagementioning
confidence: 99%
“…②The processing of fuzzy knowledge [4] Environmental chamber temperature control system, the existence of a large number of fuzzy knowledge. For example, when ∆Tem is small, it should be the refrigeration, the refrigeration quantity cannot too big.…”
mentioning
confidence: 99%