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靜液驅(qū)動(dòng)履帶車輛轉(zhuǎn)向神經(jīng)網(wǎng)絡(luò)PID控制仿真
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Steering Neural Network PID Control for Tracked Vehicle with Hydrostatic Drive
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    摘要:

    根據(jù)履帶車輛轉(zhuǎn)向運(yùn)動(dòng)學(xué)和動(dòng)力學(xué)分析,，提出轉(zhuǎn)向控制策略,，可在滿足系統(tǒng)壓力限制以及保證車輛轉(zhuǎn)向安全條件下自動(dòng)降低平均車速以保證駕駛員期望轉(zhuǎn)向半徑的準(zhǔn)確實(shí)現(xiàn),。轉(zhuǎn)向控制器由神經(jīng)網(wǎng)絡(luò)PID控制器和泵馬達(dá)排量控制器組成,。運(yùn)用Matlab/Simulink對(duì)系統(tǒng)進(jìn)行神經(jīng)網(wǎng)絡(luò)轉(zhuǎn)向控制仿真分析，仿真結(jié)果表明，與傳統(tǒng)PID控制相比較，神經(jīng)網(wǎng)絡(luò)控制輸出超調(diào)量由10.5%降至4.1%，控制響應(yīng)時(shí)間由4.8s降至2.2s,，提高了系統(tǒng)實(shí)時(shí)性和魯棒性。不同轉(zhuǎn)向工況的仿真結(jié)果表明,，采用神經(jīng)網(wǎng)絡(luò)控制可使靜液驅(qū)動(dòng)履帶車輛獲得良好的轉(zhuǎn)向穩(wěn)定性和操縱性,。

    Abstract:

    Based on steering kinematics and dynamics analysis of tracked vehicle, steering control strategy was presented to realize reducing average vehicle speed automatically while achieving the driver’s expected steering radius exactly in the case of not exceeding the system pressure threshold and secure steering. The steering controller was comprised of neural network PID controller and pump & motor displacement controller. The steering neural network control simulation was conducted by using Simulink of Matlab. The simulation results indicated that compared with conventional PID control, neural network control export overshoot reduced from 10.5% to 4.1% and control response time decreased from 4.8s to 2.2s, which meant that system real-time ability and robustness were improved. The simulation results for various steering conditions demonstrated that good steering stability and maneuverability were obtained with neural network control for tracked vehicle with hydrostatic drive.

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楊磊,馬彪,李和言.靜液驅(qū)動(dòng)履帶車輛轉(zhuǎn)向神經(jīng)網(wǎng)絡(luò)PID控制仿真[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),2010,41(7):15-20.Steering Neural Network PID Control for Tracked Vehicle with Hydrostatic Drive[J]. Transactions of the Chinese Society for Agricultural Machinery,2010,41(7):15-20.

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