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基于神經(jīng)網(wǎng)絡(luò)逆系統(tǒng)方法的汽車底盤解耦控制
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國家自然科學(xué)基金資助項目(51075112、51175135)


Vehicle Chassis Decoupling Control Based on Neural Network Inverse Method
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    摘要:

    為了消除汽車底盤各電控子系統(tǒng)間的耦合影響,，采用了一種基于神經(jīng)網(wǎng)絡(luò)逆系統(tǒng)方法的底盤解耦控制策略。對集成主動前輪轉(zhuǎn)向（AFS）,、直接橫擺力矩控制（DYC）和主動懸架（ASS）的汽車底盤系統(tǒng)進(jìn)行研究，利用Interactor算法分析了底盤系統(tǒng)的可逆性,，建立了多變量底盤系統(tǒng)的BP神經(jīng)網(wǎng)絡(luò)逆系統(tǒng)模型,，將閉環(huán)控制器與神經(jīng)網(wǎng)絡(luò)逆系統(tǒng)組成復(fù)合控制器用于改善系統(tǒng)的動態(tài)性能，并進(jìn)行了仿真驗證,。結(jié)果表明,，基于神經(jīng)網(wǎng)絡(luò)逆系統(tǒng)方法的解耦控制策略能夠消除底盤各電控子系統(tǒng)間的干涉和耦合影響，有效改善整車的操縱穩(wěn)定性,。

    Abstract:

    In order to eliminate the interference and coupling among automobile chassis electronic control subsystems, an integrated decoupling control approach based on neural network inverse method was proposed. The integration of active front steering (AFS), direct yaw moment control (DYC) and active suspension (ASS) was studied. According to Interactor algorithm, the reversibility of chassis system was analyzed and a BP neural network inverse system of the multivariable chassis system was obtained. Designing a close-loop controller and combining it with neural network inverse system, a compound controller was completed to improve dynamic performance. The simulation results showed that the proposed decoupling control approach could eliminate the interference and couple among automobile chassis electronic control subsystems, and improve the automobile handling and stability performance.

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朱茂飛,陳無畏,夏光.基于神經(jīng)網(wǎng)絡(luò)逆系統(tǒng)方法的汽車底盤解耦控制[J].農(nóng)業(yè)機(jī)械學(xué)報,2011,42(12):13-17,5. Zhu Maofei,Chen Wuwei, Xia Guang. Vehicle Chassis Decoupling Control Based on Neural Network Inverse Method[J]. Transactions of the Chinese Society for Agricultural Machinery,2011,42(12):13-17,5.

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  • 在線發(fā)布日期: 2011-12-19
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