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關(guān)鍵詞:路徑跟蹤控制; 神經(jīng)網(wǎng)絡(luò); 模糊PID; 橫向動(dòng)力學(xué)模型
中圖分類號(hào): TP273 文獻(xiàn)標(biāo)志碼: A
Vehicle Lateral Stability Control under Low Adhesion Road Conditions
TIAN Yantao, XU Fuqiang, YU Wenyan, WANG Kaige
Abstract:Aiming at the characteristic that the vehicle is more prone to instability in the snow and ice environment, the stable tracking problem of the vehicle to the reference trajectory under the low adhesion and uneven distribution condition of the road surface is studied. To address this, a fuzzy PID(Proportional-Integral-Differential) controller model based on neural network regulation and MPC(Model Predictive Control) a linearized vehicle model are designed. The controller takes the road adhesion coefficient and vehicle speed as input to construct a BP(Back-Propagation)neural network and outputs the adjustment coefficient to optimize the control performance of the PID controller. A ten-degree-of-freedom model is designed to characterize the dynamic characteristics of the vehicle in snow and ice-covered environments, and the lateral stability control of the vehicle is realized by using MPC. CarSim/Simulink is used for co-simulation experiments. Results show that the controller can significantly improve the performance of vehicle trajectory tracking. The dynamic characteristics of the vehicle under snow and ice are analyzed, and good simulation results are obtained.
Key words:trajectory tracking control; neural network; fuzzy proportional-integral-differential (PID); lateral dynamic mode
0 引 言
研究表明, 冰雪路面環(huán)境下交通事故的傷亡率增加25%, 事故率增加一倍。雪天每百萬(wàn)車輛發(fā)生的碰撞和劃傷事故為5.86起, 非雪天僅為0.41起, 僅是雪天的7%, 事故的發(fā)生與路面附著系數(shù)的降低有很大的關(guān)系[1]。絕大多數(shù)交通事故都是因?yàn)轳{駛員的錯(cuò)誤行為所導(dǎo)致[2], 而無(wú)人駕駛汽車能顯著降低交通事故發(fā)生的概率[3]。已有研究主要集中在常規(guī)工況下的穩(wěn)定性控制, 而在冰雪環(huán)境下, 由于路面附著系數(shù)降低, 其分布不均, 改變了輪胎的橫縱向受力特性, 使車輛更容易發(fā)生側(cè)滑及翻滾等問(wèn)題, 因此針對(duì)低附著路況下的車輛橫向穩(wěn)定性研究具有實(shí)際意義。
Nguyen等[4]利用T-S(Takagi-Sugeno)模糊控制處理駕駛員時(shí)變參數(shù), 用魯棒不變集處理系統(tǒng)和輸入的約束。Lauber[5]提出了根據(jù)車道保持過(guò)程中的人機(jī)協(xié)同程度, 計(jì)算對(duì)應(yīng)所需的輔助水平, 并使用對(duì)應(yīng)的調(diào)節(jié)因子調(diào)節(jié)輔助轉(zhuǎn)矩, 使用變線性參數(shù)(LPV: Linear Parameter Varying)的方法解決速度多工況問(wèn)題。……
吉林大學(xué)學(xué)報(bào)(信息科學(xué)版)
2024年1期