Thrust estimation is a significant part of aeroengine thrust control systems.The traditional estimation methods are either low in accuracy or large in computation.To further improve the estimation effect,a thrust esti...Thrust estimation is a significant part of aeroengine thrust control systems.The traditional estimation methods are either low in accuracy or large in computation.To further improve the estimation effect,a thrust estimator based on Multi-layer Residual Temporal Convolutional Network(M-RTCN)is proposed.To solve the problem of dead Rectified Linear Unit(ReLU),the proposed method uses the Gaussian Error Linear Unit(GELU)activation function instead of ReLU in residual block.Then the overall architecture of the multi-layer convolutional network is adjusted by using residual connections,so that the network thrust estimation effect and memory consumption are further improved.Moreover,the comparison with seven other methods shows that the proposed method has the advantages of higher estimation accuracy and faster convergence speed.Furthermore,six neural network models are deployed in the embedded controller of the micro-turbojet engine.The Hardware-in-the-Loop(HIL)testing results demonstrate the superiority of M-RTCN in terms of estimation accuracy,memory occupation and running time.Finally,an ignition verification is conducted to confirm the expected thrust estimation and real-time performance.展开更多
SAE划分了汽车自动驾驶的等级。为满足其L3的技术要求,从硬件和软件两个维度出发,设计汽车横向控制器EPS(Electric Power Steering,电动助力转向系统)的技术方案。首先从硬件需求出发设计了EPS的硬件系统,并对其进行可靠性分析;其次设...SAE划分了汽车自动驾驶的等级。为满足其L3的技术要求,从硬件和软件两个维度出发,设计汽车横向控制器EPS(Electric Power Steering,电动助力转向系统)的技术方案。首先从硬件需求出发设计了EPS的硬件系统,并对其进行可靠性分析;其次设计自动驾驶软件架构,分析软件子模块的功能及实现原理;最后,基于L3自动驾驶技术的需求对EPS硬件和软件进行验证。展开更多
基金co-supported by the National Natural Science Foundation of China(Nos.61890920,61890921)。
文摘Thrust estimation is a significant part of aeroengine thrust control systems.The traditional estimation methods are either low in accuracy or large in computation.To further improve the estimation effect,a thrust estimator based on Multi-layer Residual Temporal Convolutional Network(M-RTCN)is proposed.To solve the problem of dead Rectified Linear Unit(ReLU),the proposed method uses the Gaussian Error Linear Unit(GELU)activation function instead of ReLU in residual block.Then the overall architecture of the multi-layer convolutional network is adjusted by using residual connections,so that the network thrust estimation effect and memory consumption are further improved.Moreover,the comparison with seven other methods shows that the proposed method has the advantages of higher estimation accuracy and faster convergence speed.Furthermore,six neural network models are deployed in the embedded controller of the micro-turbojet engine.The Hardware-in-the-Loop(HIL)testing results demonstrate the superiority of M-RTCN in terms of estimation accuracy,memory occupation and running time.Finally,an ignition verification is conducted to confirm the expected thrust estimation and real-time performance.
文摘SAE划分了汽车自动驾驶的等级。为满足其L3的技术要求,从硬件和软件两个维度出发,设计汽车横向控制器EPS(Electric Power Steering,电动助力转向系统)的技术方案。首先从硬件需求出发设计了EPS的硬件系统,并对其进行可靠性分析;其次设计自动驾驶软件架构,分析软件子模块的功能及实现原理;最后,基于L3自动驾驶技术的需求对EPS硬件和软件进行验证。
