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Abstract
This paper addresses the control problem of heterogeneous vehicle platoons subject to disturbances and modeling errors. The objective is to guarantee spatial-geometry constraints of vehicles in a platoon. We deal with the case where a predecessor-leader following (PLF) communication topology is used and heterogeneous vehicle dynamics is subject to disturbances. To estimate the lumped disturbance, the technique of unknown input proportional multiple-integral (PMI) observer is employed such that both the state and the disturbance are simultaneously estimated. Moreover, tube-based model predictive control (TMPC) is used and the corresponding control law is composed of a feed-forward term, a feedback term, and a disturbance compensation term. The gains in the integrated control strategy are optimized by utilizing the particle swarm optimization (PSO) algorithm with an H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> performance index of an augmented error system. It is proved that the deviations between the actual system and the nominal system are bounded in a robustly positively invariant (RPI) set, that is, the main objective is guaranteed. With the proposed control strategy, simulations and comparisons are carried out. We can see that the control performance of the proposed strategy is significantly improved while the computational time is reduced compared with existing methods.
Highlights
I NTELLIGENT transportation and multi-vehicle coordination are becoming a promising area both from industry and academic research
When the system is subject to persistent disturbances, Mayne and Langson proposed tube-based model predictive control (TMPC) to solve the optimization problem [26]–[28]
The proposed control method is compared with the classical distributed model predictive control (DMPC) control scheme [16] and tube-based robust nonlinear MPC (RNMPC) method [30]
Summary
I NTELLIGENT transportation and multi-vehicle coordination are becoming a promising area both from industry and academic research. 1) The models for controller design are different. Due to the energysaving characteristics of vehicle platoons, the energy consumption may be considered as an additional control objective [8]. The platoon control is a multi-objective optimization problem under multiple physical. When the system is subject to persistent disturbances, Mayne and Langson proposed tube-based model predictive control (TMPC) to solve the optimization problem [26]–[28]. It was applied to applications such as vehicle control in [29], [30] by adding feedback terms to make the error caused by disturbance converging to an invariant set [31]–[33]. We employ the tube-based idea to design a robust controller for heterogeneous vehicle platoons subject to both modeling uncertainties and external disturbances. The rest of notations will be provided in the paper
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