2021
DOI: 10.1177/09544070211070526
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A distributed model predictive control approach to cooperative adaptive cruise control of the heterogeneous platoon

Abstract: This paper presents a distributed model predictive control algorithm to solve the cruise control problem of a heterogeneous platoon. Each following vehicle in the platoon can use the communication equipment to receive the information of the leading vehicle and its preceding adjacent one. The vehicles in the platoon are dynamically decoupled and have different dynamic parameters. Each vehicle solves a local optimal control problem independently. The cost function of each vehicle’s local optimal control algorith… Show more

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Cited by 8 publications
(2 citation statements)
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References 36 publications
(60 reference statements)
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“…In recent years, the research on CACC mainly focuses on longitudinal single-lane control, including stability analysis [ 30 , 31 , 32 , 33 , 34 ], communication problem analysis [ 35 , 36 , 37 , 38 ], heterogeneous problem analysis [ 39 , 40 , 41 , 42 ], etc. The control algorithm is mainly aimed at improving the original single-vehicle control algorithm, such as PID control, sliding mode control, and distributed model predictive control.…”
Section: Related Workmentioning
confidence: 99%
“…In recent years, the research on CACC mainly focuses on longitudinal single-lane control, including stability analysis [ 30 , 31 , 32 , 33 , 34 ], communication problem analysis [ 35 , 36 , 37 , 38 ], heterogeneous problem analysis [ 39 , 40 , 41 , 42 ], etc. The control algorithm is mainly aimed at improving the original single-vehicle control algorithm, such as PID control, sliding mode control, and distributed model predictive control.…”
Section: Related Workmentioning
confidence: 99%
“…Some new control methods have been utilized in this area. [1][2][3][4][5] For different traffic scenarios, Sawant and Chaskar developed a non-linear disturbance observerbased sliding mode control method to alleviate the peaking of control input. 6 Shojaei proposed a new control method for multiple Ackermann steering vehicle formation by combining an adaptive neural network robust controller.…”
Section: Introductionmentioning
confidence: 99%