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- W2796025370 abstract "In recent years, automatic driving control has attracted attention. To achieve a satisfactory driving control performance, the prediction accuracy of the traveling route is important. If a highly accurate prediction method can be used, an accurate traveling route can be obtained. Despite the considerable efforts that have been invested in improving prediction methods, prediction errors do occur in general. Thus, a method to minimize the influence of prediction errors on automatic driving control systems is required. This need motivated us to focus on the design of a mechanism for shaping prediction signals, which is called a prediction governor. In this study, we first extended our previous study to the input-affine nonlinear system case. Then, we analytically derived a solution to an optimal design problem of prediction governors. Finally, we applied the solution to an automatic driving control system, and demonstrated its usefulness through a numerical example and an experiment using a radio controlled car." @default.
- W2796025370 created "2018-04-13" @default.
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- W2796025370 date "2018-04-04" @default.
- W2796025370 modified "2023-09-23" @default.
- W2796025370 title "Prediction Governors for Input-Affine Nonlinear Systems and Application to Automatic Driving Control" @default.
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- W2796025370 doi "https://doi.org/10.3390/robotics7020016" @default.
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