Yasuhiro Fuchikawa

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— For cleaning silicon wafers via the RCA clean, temperature control is important for stable cleaning performance, but difficult owing that the RCA solutions expose nonlinear and time-varying exothermic chemical reactions. So far, the MSPC (model switching predictive controller) using the CAN2 has been developed and the effectiveness has been validated,(More)
The competitive associative net called CAN2-2 has been presented for learning to approximate time-varying dynamics of a plant in order to control the plant. Although the learning method has been shown effective in the previous studies, it uses the gradient method involving local minima problems. To overcome the problems, we here consider asymptotic(More)
This paper illustrates and analyzes the competitive associative net called CAN2 applied to model-switching control of the temperature of RCA cleaning solutions, where the RCA clean is the industry standard way to clean silicon wafers and the temperature control is important for a stable cleaning performance. Since the control is dii-cult owing that the RCA(More)
The outdoor service robot which we call OSR-01 is presently under development intending for cleaning up urban areas by means of collecting discarded trash such as PET bottles, cans, plastic bags and so on. We, in this paper , describe the architecture of OSR-01 consisting of hard-wares such as sensors, a manipulator, driving wheels, etc. for searching for(More)
— Cross-validation and bootstrap, or resampling methods in general, are examined for applying them to optimizing the number of units of competitive associative nets called CAN2. There are a number of resampling methods available, but the performance depends on the neural network to be applied and functions to be learned. So, we apply several resampling(More)
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