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Guaranteed Cost Model Predictive Control-based Driver Assistance system for vehicle stabilization under tire parameters uncertainties

机译:轮胎参数不确定性下基于稳定成本模型预测控制的驾驶员辅助系统

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Road traffic crashes have been the leading cause of death among young people. Most of these accidents occur when the driver becomes distracted and a loss-of-control situation occurs. Steer-by-Wire systems were recently proposed as an alternative to mitigate such accidents. This technology enables the decoupling of the front wheel steering angles from the driver hand wheel angle and, consequently, the measurement of road/tire friction limits and the development of novel control systems capable of ensuring vehicle stabilization and safety. However, vehicle safety boundaries are highly dependent on tire characteristics which vary significantly with temperature, wear and the tire manufacturing process. Therefore, design of autonomous vehicle and driver assistance controllers cannot assume that these characteristics are constant or known. Thus, this paper proposes a Guaranteed Cost Model Predictive Controller Driver Assistance System able to avoid front and rear tire saturation and to track the drivers intent up to the limits of handling for a vehicle with uncertain tire parameters. Simulation results show the performance of the proposed approach under time-varying uniformly distributed disturbances.
机译:道路交通事故已成为年轻人死亡的主要原因。这些事故大多数发生在驾驶员分心并失控的情况下。最近提出了线控转向系统作为减轻此类事故的替代方法。这项技术可以使前轮转向角与驾驶员手轮角解耦,从而测量道路/轮胎摩擦极限,并开发出能够确保车辆稳定和安全的新型控制系统。然而,车辆安全边界高度依赖于轮胎特性,该轮胎特性随温度,磨损和轮胎制造过程而显着变化。因此,自动驾驶车辆和驾驶员辅助控制器的设计不能假定这些特性是恒定的或已知的。因此,本文提出了一种保证成本模型预测控制器驾驶员辅助系统,该系统能够避免前后轮胎饱和,并且能够跟踪驾驶员的意图,直至对于具有不确定轮胎参数的车辆的操作极限。仿真结果表明了该方法在时变均匀分布扰动下的性能。

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