基于因果律分析的高超声速飞行器执行器受限情形下的智能控制研究

For practical hypersonic flight control, actuator constraint should be considered. Otherwise it may cause bad tracking performance or even make the system unstable since the desired control input could not be implemented. Based on equivalent prediction model, this project focuses on the novel intelligent controller design for the longitudinal dynamics of hypersonic flight vehicle with constrained actuator. Firstly, the causality lying in system states, control inputs and system outputs is studied to formulate the equivalent prediction model for the original hypersonic flight dynamics.Secondly, due to the aerodynamic changes and unmodelled dynamics, the complex system uncertainty is composed of static part and fast dynamic part. Accordingly, the neural network is integrated with statistic method to formulate the composite estimation scheme. Finally, taking actuator constraint into consideration, based on aforementioned equivalient prediction model and composite estimation scheme, auxiliary error dynamics are involved to construct the intelligent controller while the stability of the closed-loop system will be analyzed. The related modeling, estimation and controller design will be verified via Matlab/Simulink and semi-physical simulation platform. Through this project, it is supposed to provide new progress for intelligent adaptive control of hypersonic flight vehicle in presence of actuator constraint.

在实际的高超声速飞行器控制设计中，应考虑执行器受限情形，否则期望的控制输入不能被很好的执行，会导致控制跟踪性能变差，甚至破坏飞行器的稳定性。本项目针对高超声速飞行器纵向通道模型，考虑执行器受限提出一种基于等价预测模型的智能自适应控制方法。首先，通过因果律分析来研究当前控制输入与系统状态、系统输出的关系，建立原系统的等价预测模型；其次，考虑气动特性变化和未建模动态等因素影响，采用神经网络与统计学方法结合的方式对系统不确定的静态和动态快变部分进行复合自适应估计；最后，基于上述建模和估计策略，利用辅助误差动力学，研究执行器受限情形的智能控制器设计和稳定性分析。以上研究将通过 Matlab/Simulink和半物理仿真平台进行验证。通过该项目研究，将在高超声速飞行器执行器受限情形下的智能自适应控制等关键理论和技术方面取得一定的进展。

在实际的高超声速飞行器控制设计中，应考虑执行器受限情形，否则期望的控制输入不能被很好的执行，会导致控制跟踪性能变差，甚至破坏飞行器的稳定性。本项目针对高超声速飞行器纵向通道模型，考虑执行器受限提出一种基于等价预测模型的智能自适应控制方法。首先，通过因果律分析来研究当前控制输入与系统状态、系统输出的关系，建立原系统的等价预测模型；其次，考虑气动特性变化和未建模动态等因素影响，采用神经网络与统计学方法结合的方式对系统不确定的静态和动态快变部分进行复合自适应估计；最后，基于上述建模和估计策略，利用辅助误差动力学，研究执行器受限情形的智能控制器设计和稳定性分析。以上研究通过 Matlab/Simulink和半物理仿真平台进行验证。通过该项目研究，在高超声速飞行器执行器受限情形下的智能自适应控制等关键理论和技术方面取得一定的进展。依托该项目发表SCI论文15篇，ESI高被引论文8篇；获得授权发明专利7项。