Event-triggered sliding mode control for aero-engine distributed systems
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摘要:
针对存在时变时延和随机丢包的航空发动机分布式控制系统，在具有外部扰动的情况下，设计了保证系统渐近稳定的事件触发滑模控制器。为了提高资源的利用率，引入了动态事件触发机制（DETM）来调度采样信号的传输。为了便于滑模面的建立，设计了状态观测器，并基于观测状态构造了积分滑模面。通过李雅普诺夫方法，得到了稳定性准则，并给出了线性矩阵不等式（LMIs）形式的控制器、观测器、事件触发器的参数计算方法。随后设计了滑模控制律，确保了滑模面的可达性。此外，为了提高LMIs的可行性，提出了基于iL-SHADE算法的LMIs参数优化方法。仿真结果表明，在给定的控制框架下，闭环系统能够保证较好的控制性能。在给定的仿真条件下，减少了96.5%的信号传输，极大节省了通信资源。
Abstract:An event-triggered sliding mode controller was designed to ensure the asymptotic stability of the aero-engine distributed control systems subjecting to time-varying delay, random packet dropout and external disturbances. To improve the resources utilization, a dynamic event-triggered mechanism (DETM) was introduced to schedule the transmission of the sampled output signals. To facilitate the establishment of sliding mode surface, an observer was designed and an integral sliding mode surface was constructed based on the observed states. By Lyapunov method, the stability criterion was obtained, and the parameter calculation method of controller, observer and DETM was presented in form of linear matrix inequalities (LMIs). Then the sliding mode control law was designed to ensure the accessibility of the sliding surface. In addition, an LMI parameters adjustment method based on iL-SHADE was proposed to improve the feasibility of LMIs. The simulation results showed that the closed-loop system can guarantee better control performance for the given control structure. And under the given simulation conditions, the signal transmission was reduced by 96.5%, greatly saving the communication resources.
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图 1 基于事件触发的航空发动机分布式系统架构
Figure 1. Structure of event-triggered aero-engine distributed control systems
图 5 系统状态
${\boldsymbol{x}} （t） $ 和估计值${\boldsymbol{\hat x}} （t） $ Figure 5. States
${\boldsymbol{x}} （t） $ and estimates${\boldsymbol{\hat x}} （t） $ 
图 6
${\boldsymbol{u}} （t） $ 、${\boldsymbol{s}} （t） $ 和$\eta （t） $ 的曲线Figure 6. Curves of
${\boldsymbol{u}} （t） $ ,${\boldsymbol{s}} （t） $ and$\eta （t） $ 
图 7 不同工作条件下
${{\boldsymbol{x}}_2}$ 的响应曲线Figure 7. Response curves of
${{\boldsymbol{x}}_2}$ under different working conditions -
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