Dynamic predictor-based adaptive cruise control |
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| Institution: | 1. Department of Automatic Control, CINVESTAV-IPN, Mexico City 07360, Mexico;2. Department of Mechatronic Engineering, ITST, Instituto Tecnológico Superior de Teziutlán, Teziutlán, Mexico;3. Department of Mechanical Engineering, DICIS, Universidad de Guanajuato, Salamanca, Mexico;1. School of Electronic and Information Engineering, Suzhou University of Science and Technology, Suzhou, 215009, PR China;2. Department of Mechanical Engineering, Politecnico di Milano, Milan, 20156, Italy;3. Guangxi Key Lab of Multi-Source Information Mining and Security, Guangxi Normal University, Guilin, 541004, PR China;1. School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, China;2. Institute of Electric Vehicle Driving System and Safety Technology, University of Electronic Science and Technology of China, Chengdu, 611731, China;1. School of Artificial Intelligence, Anhui University, Hefei 230601, China;2. School of Reliability and Systems Engineering, Beihang University, Beijing 100191, China;3. School of Automation, Southeast University, Nanjing 210096, China;1. School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China;2. Institute of Artificial Intelligence, Beihang University, Beijing 100191, China;3. School of Cyber Science and Technology, Beihang University, Beijing 100191, China |
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| Abstract: | We study the stabilization problem of a platoon of Adaptive Cruise Control (ACC) vehicles in the presence of input-delay. We use a dynamic predictor for input-delay compensation, a filtered version of the standard finite spectrum assignment method that overcomes robustness issues, in particular those raised by the approximation of distributed time-delay terms. Each vehicle must achieve the velocity of the preceding vehicle while ensuring a safe inter-vehicular distance established by a time headway-based spacing policy. To this end, a proportional-integral type controller combined with a dynamic predictor is added to each vehicle in the platoon that guarantees stability and zero steady-state error. String stability property of the closed-loop system, i.e., the platoon’s ability to attenuate fluctuations arising in the motion of the leading vehicle, is analyzed using a frequency domain framework. The effectiveness of the proposed control scheme is illustrated with simulation results of a platoon of five vehicles. |
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