期刊
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
卷 19, 期 7, 页码 8418-8426出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TII.2022.3217470
关键词
Dynamic event-trigger (DET); fault-tolerant control; model-free adaptive control (MFAC); vehicular platooning control
This article studies the dynamic event-triggered fault-tolerant model-free adaptive platooning control problem in vehicle platoon systems subject to sensor faults. A novel redefined output is introduced to assist in proving the synchronous tracking of the position and velocity. The equivalent dynamic linearization technique is used to transform the nonlinear vehicular platooning systems into a linear data model, and an observer is designed to estimate the pseudo-partial derivative parameter and eliminate symbol restriction on it. DET mechanism is introduced to save network resources effectively, and the neural network method is applied to handle sensor faults for safe vehicle driving. A novel DET-based fault-tolerant MFAPC strategy is developed to realize vehicular position and velocity tracking using only input-output data. An example is provided to demonstrate the effectiveness of the designed MFAPC framework.
This article addresses the dynamic event-triggered (DET) fault-tolerant model-free adaptive platooning control (MFAPC) problem of vehicle platoon systems subject to sensor faults. First of all, a novel redefined output is introduced to assist in proving the synchronous tracking of the position and velocity. Based on which, the equivalent dynamic linearization technique is used for transforming the nonlinear vehicular platooning systems into an linear data model. Then, an observer is designed to introduce the estimation of the pseudo-partial derivative (PPD) parameter, which can also eliminate the symbol restriction on it. In addition, a DET mechanism is introduced to save network resources more effectively, and the neural network method is applied to deal with the sensor faults for the safe vehicle driving. Further, a novel DET-based fault-tolerant MFAPC strategy is developed to realize the vehicular position and velocity tracking only using the input-output data. At last, an example is provided to prove the effectiveness of designed MFAPC framework.
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