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區(qū)域交通智能車(chē)輛導(dǎo)航控制技術(shù)
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    摘要:

    通過(guò)系統(tǒng)辨識(shí)實(shí)驗(yàn)得到車(chē)輛轉(zhuǎn)向系統(tǒng)動(dòng)態(tài)特性方程，結(jié)合車(chē)輛預(yù)瞄運(yùn)動(dòng)學(xué)模型和二自由度轉(zhuǎn)向動(dòng)力學(xué)模型建立基于視覺(jué)預(yù)瞄的轉(zhuǎn)向動(dòng)力學(xué)控制數(shù)學(xué)模型，根據(jù)線性二次型最優(yōu)控制理論設(shè)計(jì)的最優(yōu)控制器能穩(wěn)定跟蹤直線路徑。采用模糊控制快速跟蹤弧線導(dǎo)航路徑，結(jié)合車(chē)輛轉(zhuǎn)向系統(tǒng)當(dāng)前狀態(tài)和最快動(dòng)態(tài)響應(yīng)能力建立車(chē)輛弧線跟蹤時(shí)的變結(jié)構(gòu)控制輸出集。針對(duì)JLUIV-Ⅴ型區(qū)域交通智能車(chē)輛部分狀態(tài)變量的不可測(cè)性，根據(jù)Kalman濾波理論構(gòu)造狀態(tài)觀測(cè)器。仿真和試驗(yàn)結(jié)果表明：該控制技術(shù)在區(qū)域交通智能車(chē)輛戶外路徑跟蹤過(guò)程中平穩(wěn)、可靠。

    Abstract:

    Establishing the vehicle steering dynamic equation by system identification experiment firstly, then combined with preview kinematics model and two-degree steering dynamic model of vehicle, therefore the vehicle steering control mathematics model based on preview kinematics was established. The optimal controller could trace the line path well. Adopting fuzzy control to fast-track the curve path, combined with the current state and the fastest dynamic response capability of the vehicle steering system, the variable structure control output set of vehicle petersen tracking was established. The Kalman observer was designed to solve the unmeasurable state variable for JLUIV-Ⅴ(CyberCar). The results of both simulation and experiment showed that the control technology could trace the path smoothly and reliably during the outdoor path tracking process of CyberCar.

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王榮本,張榮輝,金立生,郭烈.區(qū)域交通智能車(chē)輛導(dǎo)航控制技術(shù)[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),2007,38(7):39-42.[J]. Transactions of the Chinese Society for Agricultural Machinery,2007,38(7):39-42.

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