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Safe Fault Reproductions for the Fuel Metering Valve Sticking in Aeroengines

IEEE-ASME TRANSACTIONS ON MECHATRONICS 2025年第2期30卷 1601-1606页

作者： Yu, Liang Cao, Jiaxin Zhu, Ye Sun, Xi-Ming Dalian Univ Technol Sch Control Sci & Engn Dalian 116033 Peoples R China AECC AeroEngine Control Syst Inst Wuxi 214125 Peoples R China

In an aeroengine, precise regulation of fuel supply relies on controlling the flow area of the fuel metering valve (FMV). However, the intrusion of pollutants into the gap between the spool and sleeve of the FMV can lead to the FMV motion becoming stuck, a phenomenon referred to as the FMV sticking (FMVS). Due to the infrequent FMVS occurrences and the potential damages to aeroengine from artificial induction, FMVS data are scarce, impeding analysis and resolution for FMVS. To address this issue, this article investigates the safe reproduction for FMVS. We propose introducing an appropriate bias into the control law output in the FMV control loop, allowing for the reconstructions of resultant forces on the FMV under sticking, thereby reproducing the FMV motions under sticking. The implementation of this method only requires minor adjustments to the code of control law, ensuring ease of implementation and prevention of aeroengine damages. Theoretical validation affirms its effectiveness in reproducing the FMVS at any level. hardware-in-loop experiments demonstrate the effectiveness, safety, and ease of implementation of the proposed method.

关键词： Electronic control in aeroengine fault reproduction hardware-in-loop experiment valve sticking Electronic control in aeroengine fault reproduction hardware-in-loop experiment valve sticking

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Energy management strategy research on a hybrid power system by hardware-in-loop experiments

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APPLIED ENERGY 2013年 112卷 1311-1317页

作者： He, Hongwen Xiong, Rui Zhao, Kai Liu, Zhentong Beijing Inst Technol Sch Mech Engn Natl Engn Lab Elect Vehicles Beijing 100081 Peoples R China

A fuzzy logic-based energy management strategy for a hybrid power system used in electric vehicles was developed and verified in this paper. First, the topology structure of a hybrid power system was put forward that the ultracapacitors connected with the battery pack in parallel after a bidirectional DC/DC converter. To improve the systematic efficiency, a fuzzy logic-based energy management strategy was designed and the control model was built. We proposed an active electricity management module for the ultracapacitors on the basis of the real-time vehicle velocity. Then, the vehicle model, the interface model of the electrical load and the xPC Target were built with the Simulink/State flow soft. Finally, the hybrid power/energy system-in-loop simulation experiment was carried out to verify the energy management strategy under the Urban Dynamometer Driving Schedule (UDDS) dynamic driving cycle. The results show the proposed fuzzy logic-based energy management strategy can ensure the battery pack working in high efficiency range and show better performance than the traditional logic threshold-based control strategy. The hybrid power system's electricity economy was improved by 4.1% and the bad influences of the high-current discharging and charging on battery pack were avoided successfully. (C) 2012 Elsevier Ltd. All rights reserved.

关键词： xPC Target hardware-in-loop experiment Battery pack Hybrid power/energy system Electric vehicles

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Power Management Comparison for a Dual-Motor-Propulsion System Used in a Battery Electric Bus

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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2017年第5期64卷 3873-3882页

作者： Zhang, Chengning Zhang, Shuo Han, Guangwei Liu, Haipeng Beijing Inst Technol Sch Mech Engn Beijing 100081 Peoples R China Beijing Inst Technol Collaborat Innovat Ctr Elect Vehicles Beijing 100081 Peoples R China Henan Polytech Univ Sch Mech Power Engn Jiaozuo 454000 Peoples R China

The efficiency performance of multi-motor-driven system highly depends on the power management. Three aspects of contribution have been made in this study. 1) A predictive power management for a DMPS is developed. To improve the performance of the predictive power management, an adaptive velocity predictor is proposed and the coefficients of proposed predictor can update its parameters according to identified driving patterns. Simulation results show that the new velocity predictor have best prediction performance compared with traditional predictors. 2) A neural network based power management is proposed. According to the optimization results of dynamic programming, radial-basis-function neural network is trained. The input dimensions and the number of hidden layer neurons of the neural network are optimized. 3) The performance of proposed control strategies are compared with three different drive cycles including MANHATTAN cycle, Japanese 1015 cycle, and UDDSHDV cycle. Simulation results indicate that compared with original control strategy, the predictive control strategy and neural network based control strategy show better efficiency performance. The neural network based strategy is verified by hardware-in-loop experiment and experiment results indicate that the control performance in real hardware shows similar property with simulation results.

关键词： Dual motor electric vehicle (EV) hardware-in-loop experiment neural network (NN) power management speed prediction

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Gain-scheduling control of dynamic lateral lane change for automated and connected vehicles based on the multipoint preview

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IET INTELLIGENT TRANSPORT SYSTEMS 2020年第10期14卷 1338-1349页

作者： Nie, Zhigen Li, Zhongliang Wang, Wanqiong Zhao, Weiqiang Lian, Yufeng Outbib, Rachid Kunming Univ Sci & Technol Fac Transportat Engn Kunming 650500 Yunnan Peoples R China Aix Marseille Univ CNRS UMR 7020 LIS Lab F-13397 Marseille France Jilin Univ State Key Lab Automobile Dynam Simulat Changchun 130022 Jilin Peoples R China Changchun Univ Technol Sch Elect & Elect Engn Changchun 130012 Jilin Peoples R China

Dynamic lateral lane change (DLLC) control of automated and connected vehicles (ACVs) is challenging because of the time-varying and complex properties of the traffic environment. This study proposes a DLLC control strategy combining dynamic trajectory planning and tracking. According to the real-time longitudinal accelerations and velocities of multiple surrounding vehicles, as well as the real-time states of the ACVs, the safe trajectory reference of DLLC is obtained by solving a case-dependent constrained optimisation problem. The lane changing efficiency, vehicle stability and passenger comfort are considered jointly in the trajectory planning. Then, the dynamic trajectory reference is tracked through a gain-scheduling control algorithm combining previewed trajectory feed-forward and ACVs states feedback. Gain-scheduling control algorithm based on a linear time-varying form is utilised to achieve the precise control of the different velocities and improve the real-time ability of the algorithm. The proposed strategy is tested through software and hardware-in-loop experiments, and in different test scenarios. The results of simulations and experiments show that the proposed control strategy can achieve a satisfactory performance of DLLC. The lane changing efficiency, safety, passenger comfort and vehicle stability are verified in complex traffic environments.

关键词： predictive control road vehicles optimisation state feedback time-varying systems stability linear systems road traffic control gain control hardware-in-the loop simulation control engineering computing traffic engineering computing road safety case-dependent constrained optimisation problem lane changing efficiency vehicle stability passenger comfort dynamic trajectory reference gain-scheduling control algorithm linear time-varying form complex traffic environments automated vehicles multipoint preview dynamic lateral lane change control connected vehicles dynamic trajectory planning real-time longitudinal accelerations ACV states feedback DLLC control software-in-loop experiment hardware-in-loop experiment feedforward trajectory

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Perturbation observer based fractional-order PID control of photovoltaics inverters for solar energy harvesting via Yin-Yang-Pair optimization

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ENERGY CONVERSION AND MANAGEMENT 2018年 171卷 170-187页

作者： Yang, Bo Yu, Tao Shu, Hongchun Zhu, Dena Zeng, Fang Sang, Yiyan Jiang, Lin Kunming Univ Sci & Technol Fac Elect Power Engn Kunming 650500 Yunnan Peoples R China South China Univ Technol Coll Elect Power Guangzhou 510640 Guangdong Peoples R China Guangdong Key Lab Clean Energy Technol Guangzhou 510640 Guangdong Peoples R China Univ Liverpool Dept Elect Engn & Elect Liverpool L69 3GJ Merseyside England

In this paper, a novel perturbation observer based fractional-order PID (PoFoPID) control scheme is proposed for a grid-connected Photovoltaics (PV) inverter to harvest the available maximum solar energy from the PV arrays under various atmospheric conditions. A high-gain state and perturbation observer (HGSPO) is adopted to efficiently estimate the aggregated effect of PV inverter nonlinearities, parameter uncertainties, unmodelled dynamics, stochastic fluctuation of atmospheric conditions, and external disturbances. Then, a fractional-order PID (FoPID) control is employed to fully compensate the perturbation estimate and to significantly improve the dynamical responses of the closed-loop system, in which Yin-Yang-Pair optimization (YYPO) algorithm is used to rapidly and effectively seek its optimal control parameters. Inspiringly, PoFoPID control can simultaneously own the elegant merits of global control consistency and robustness of perturbation observer based control, high reliability and simple structure of FoPID control, as well as the global optimality of YYPO algorithm. Four case studies including the solar irradiation change, temperature variation, power grid voltage drop, and inverter parameter uncertainties are undertaken. Simulation results verify the effectiveness and superiority of the PoFoPID control compared to that of PID control, FoPID control, feedback linearization control (FLC), and sliding-mode control (SMC), respectively. At last, a dSpace based hardware-in-loop (HIL) experiment is carried out to validate the implementation feasibility of PoFoPID control.

关键词： Solar energy harvesting PV inverter Perturbation observer based fractional-order PID control Yin-Yang-Pair optimization hardware-in-loop experiment

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Improved model reference-based adaptive nonlinear dynamic inversion for fault-tolerant flight control

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INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL 2023年第17期33卷 10328-10359页

作者： Li, Yu Liu, Xiaoxiong Ming, Ruichen Li, Kecheng Zhang, Weiguo Northwestern Polytech Univ Automat Xian Shaanxi Peoples R China Northwestern Polytech Univ Automat Dongxiang Rd Xian Shaanxi Peoples R China

Due to lack of robustness, Nonlinear Dynamic Inversion (NDI) control cannot resist the influence of disturbances. In this paper, an adaptive fault-tolerant control method, called Improved Model Reference-based Adaptive NDI (IMR-ANDI), is proposed and applied to develop a fault-tolerant flight controller to improve robustness to faults and disturbances. To improve the estimation accuracy, this paper also modified the piecewise-constant adaptation, which improves the accuracy of adaptive estimation without increasing the sampling frequency. Moreover, a low-pass filter is introduced to the control law creatively to weaken the disturbance of high-frequency dynamics to the adaptation, which balances the dynamic performance and robustness as well as prevents the system oscillation. Finally, a fault-tolerant flight controller is developed based on the IMR-ANDI and verified under the actuator fault and center of gravity variations. All simulation and hardware-in-the-loop experiment results conform to the theoretical analysis, indicating that the developed IMR-ANDI fault-tolerant controller is robust to faults and disturbances and can achieve expected control performance.

关键词： fault-tolerant flight controller hardware-in-loop experiment improved model reference-based adaptive NDI improved piecewise-constant adaptation low-pass filter

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Performance recovery control of aero-engine based on stochastic configuration network 36

Performance recovery control of aero-engine based on stochas...

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36th Chinese Control and Decision Conference (CCDC)

作者： Yu, Zijun Ma, Yanhua Du, Xian Sun, Ximing Dalian Univ Technol Sch Control Sci & Engn Dalian Liaoning Peoples R China Dalian Univ Technol Sch Microelect Dalian Liaoning Peoples R China

ISBN: (纸本)9798350387780;9798350387797

In this paper, a performance recovery control method is proposed for the aero-engines under performance degradation. Firstly, in order to improve the estimation accuracy of the degradation factors and thrust for the aero-engines with less sensors, a Kalman Filter based on stochastic configuration network(SCN) is proposed. Then, a performance recovery control method is developed based on the estimated degradation factors and thrust. It features by strong self-learning and adaptive ability, which could achieve nearly the same thrust as the aero-engine without performance degradation. Finally, experimental results show that the proposed method can not only restore the thrust of aero-engine effectively, but also demonstrate a dynamic adjustment time of 3s without overshoot.

关键词： Performance degradation Performance recovery control Kalman Filter stochastic configuration network hardware-in-loop experiment

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