Parameter tuning of active disturbance rejection control for aeropropulsion systems test facility under complex scenarios
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摘要:
面对航空推进系统测试装置高空环境模拟中强流量冲击、显著非线性、未建模动态及复杂试验场景带来的控制难题, 亟需在ADRC强抗扰、弱模型依赖优势基础上，进一步突破固定参数和经验试凑调参对控制性能的制约。为此，提出了一种基于时间尺度与空间尺度变换的参数整定方法来实现高效的ADRC参数整定。具体地，通过建立系统的时间/空间尺度与ADRC三大核心模块跟踪微分器（TD）、扩张状态观测器（ESO）以及非线性状态误差反馈控制律（NLSEF）的控制参数映射关系，构建完整的ADRC参数整定规则，并分别对各模块进行仿真验证与性能分析。试验结果表明，所提方法显著简化了ADRC参数整定过程并提高了参数获取准确性。相较于基于带宽法的线性ESO-ADRC，在所提参数整定算法下，线性ESO-ADRC的稳态阶段平均绝对误差由0.35降至0.17，过渡态最大压力波动由0.42 kPa降至0.22 kPa，最大压力恢复时间由6.5 s缩短至4.0 s；进一步地，非线性NESO-ADRC的上述指标分别优化至0.12、0.13 kPa和2.7 s，表明所提方法能够有效提升压力控制性能，从而保障航空发动机飞行试验的可靠性。
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关键词:
- 航空推进系统测试装置 /
- 高空环境模拟 /
- 复杂场景 /
- 自抗扰控制 /
- 参数整定
Abstract:In high-altitude environment simulation for aerospace propulsion system test facilities, severe flow-rate shocks, pronounced nonlinearities, unmodeled dynamics, and complex test scenarios pose significant challenges to control performance, thereby motivating the need to overcome the limitations of fixed-parameter ADRC and experience-based trial-and-error tuning. To address this challenge, an efficient parameter self-tuning method for ADRC is proposed, based on temporal and spatial scale transformations, to improve control performance of aeropropulsion systems test facility under complex scenarios. Specifically, this method establishes quantitative mapping relationships between the system’s temporal/spatial scales and the parameters of the three core ADRC modules: the tracking differentiator (TD), the ex-tended state observer (ESO) and the nonlinear state error feedback (NLSEF). The simulation results for each module validate the effectiveness and adaptability of the proposed approach. Finally, the proposed self-tuning approach is applied to the pressure control of aeropropulsion systems under different scenarios. Experimental results show that the proposed method significantly simplifies the ADRC parameter-tuning process and improves the accuracy of parameter acquisition. Compared with the bandwidth-based linear ESO-ADRC, under the proposed parameter-tuning algorithm, the steady-state mean absolute error of the linear ESO-ADRC is reduced from 0.35 to 0.17, the maximum pressure fluctuation during the transient phase is reduced from 0.42 kPa to 0.22 kPa, and the maximum pressure recovery time is shortened from 6.5 s to 4.0 s. Furthermore, the corresponding indices of the nonlinear NESO-ADRC are further improved to 0.12, 0.13 kPa, and 2.7 s, respectively. These results indicate that the proposed method can effectively enhance pressure control performance, thereby ensuring the reliability of aeroengine flight tests.
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图 1 航空推进系统测试装置原理示意图
Figure 1. Schematic diagram of aeropropulsion systems test facility
图 4 航空推进系统测试装置ADRC参数整定
Figure 4. ADRC parameter tuning for the aeropropulsion systems test facility
图 9 输入扰动的频域特性表现
Figure 9. Results of the frequency-domain characteristics of the input disturbance
图 10 输出噪声的频域特性表现
Figure 10. Results of the frequency-domain characteristics of the output noise
图 13 试验场景1下ADRC压力控制表现
Figure 13. Pressure control performance of ADRC under test scenario 1
图 14 场景2下基于带宽法ADRC压力控制表现
Figure 14. Pressure control performance of ADRC with bandwidth tuning method under test scenario 2
图 15 基于时间与空间尺度方法的ADRC参数整定过程
Figure 15. Parameter tuning process of ADRC based proposed temporal and spatial scale method
图 16 场景2下两组参数ADRC压力控制表现
Figure 16. Pressure control performance of ADRC with two parameter sets under test scenario 2
图 17 场景2新参数下线性/非线性ADRC压力控制表现
Figure 17. Pressure control performance of linear/nonlinear ADRCs with new parameters under test scenario 2
表 1 场景1试验
Table 1. Test for scenario 1
阶段 时间/s 飞行马赫数 压力/kPa 流量/（kg/s） 匀速平飞 0～100 0～0 101.3～101.3 60～20 机动飞行 100～250 0～0.5 101.3～54 20～10 推力瞬变 250～300 0.5～0.5 54～54 10～20 
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表 2 场景2试验
Table 2. Test for scenario 2
阶段 时间/s 飞行马赫数 压力/kPa 流量/（kg/s） 匀速平飞 0～100 0～0 101.3～101.3 60～20 机动飞行 100～250 0～0.9 101.3～54 20～10 推力瞬变 250～300 0.5～0.5 54～54 48～84
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表 3 试验结果量化比较
Table 3. Quantitative comparison of test result
方法 $ E_{{\mathrm{ma}}} $ 最大压力
波动/kPa最大压力
恢复时间/s线性ESO-ADRC
（带宽法）0.35 0.42 6.5 线性ESO-ADRC
（所提方法）0.17 0.22 4.0 非线性ESO-ADRC
（所提方法）0.12 0.13 2.7
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