PDF《博士学位论文公示材料》

凭借上述成果,给出了不依赖任何模型参数 的输出反馈容错 LQR 最优控制方案(从工程的角度来看,该方案与文献[1]报导的需要已知被控系统输 入矩阵的状态反馈容错控制方法相比,更具可行性) ;

最后用两个数值例子和一个直流电机控制系统的 仿真例子,证实了所提方法的有效性和优点. ―2―

第四章利用残差产生器的数据驱动形式,开发了模型未知 LTI 系统的输出反馈 L2 控制器;

针对由 该L2 控制器构建的闭环系统, 基于残差产生器的参数化矩阵, 给出了用于实现跟踪控制的前置滤波器;

进一步,通过改进上述时变值函数逼近结构,设计了数据驱动输出反馈容错 L2 控制算法,并由两个仿 真例子验证了以上研究结果的有效性及优越性.

第五章针对具有随机测量噪声和过程噪声的模型未知线性系统,利用有限次求和形式的期望算子, 构造了基于新息协方差矩阵的摄动 Bellman 方程;

继而开发了一种新的输出反馈 ADP 算法 (与其他 ADP 方法相比,在均值为零的平稳白噪声条件下,该算法可确保值函数收敛到最优性能指标) ;

随后设计了 故障检测机制和跟踪控制策略;

在此基础上,提出了考虑上述噪声影响的数据驱动容错近似最优控制 方案;

接着,通过直流电机速度控制实验,展示了该方案的有效性和实用性.

第六章提出了一种利用较少存储空间和计算资源在线迭代辨识被控对象能观标准型、状态观测器 和残差产生器的方法;

其次,设计了数据驱动容错补偿控制器;

然后,针对闭环 PID 系统的执行器故 障和被控对象故障,基于故障检测机制开发了容错补偿计划(不同于针对开环系统设计的容错控制方 法,该计划是为闭环系统开发的,因此经轻微改进,传统 PID 控制系统就可具备容错能力,而且经长 期实践检验认可的原有 PID 控制器也被保留下来) ;

进而实施了直流伺服系统容错控制实验.

第七章使用 PID 控制器的参数和状态向量建立了一个新型残差产生器,并给出了它的数据驱动设 计方法;

基于此,开发了一套可完全解耦地估计模型未知 PID 系统中同时存在的多个传感器漂移故障 的数据驱动迭代估计程序(该程序能够从残差信号中连续、无偏地估计出这些故障,相比之下,现有 其他数据驱动方法仅能发布有偏的估计值) ;

进一步,提出了利用故障估计值校正跟踪误差消除传感器 漂移故障对 PID 系统跟踪性能影响的办法;

在此基础上,设计了具有大时间常数和纯滞后环节的变参 数PID 系统中传感器故障的容错补偿方案;

最后,运用连续搅拌加热水箱数学模型,仿真验证了所提 方法的有效性,而且通过双室电加热炉的容错控制实验阐明了该方案的实用价值.

第八章总结了本文的主要创新点,并对下一步工作进行了展望. ―3― 论文摘要(英文) Due to the increasing complexity and scale of control systems, it is getting harder to guarantee their long-term reliable operation. An extremely small malfunction that is not tackled appropriately may cause catastrophic consequences, particularly in the domains closely related to personal and property safety, such as aviation, aerospace, and nuclear power. To ensure that the performance of the whole system is still acceptable when faults occur, fault-tolerant control (FTC) techniques have gotten more attention in the above domains. During the past three decades, analytical redundancy-based FTC methods have been studied extensively. Instead of employing hardware redundancy, such methods make use of the mathematical models of the controlled plants to achieve the functional redundancy of the components in control systems and further develop controllers for the purpose of FTC. However, since it is very difficult to build the accurate models of certain complex industrial plants (e.g., large-scale chemical processes) in terms of the physical and mathematical knowledge, the model-based FTC approaches cannot handle properly the faults arising in these plants. On the other hand, with the aid of the rapid development of information technology, a great number of input-output data of the aforementioned plants can be derived in the industrial field. Because the intrinsic characteristics of the plants are contained in the obtained data, how to exploit effectively these data to fulfill the FTC (namely data-driven FTC) has become a research hotspot in both the academic and industrial communities. Therefore, the study of data-driven FTC has theoretical and practical significance. Unfortunately, the relevant research is still in its early stage and many open problems remain. To this end, by virtue of approximate dynamic programming (ADP) and subspace identification techniques, the dissertation is concerned with the problem of data-driven output-feedback FTC for unknown linear dynamic systems. As a result, Chapters 3-5 present fault-tolerant optimal control methods for the controlled plants in the design phase, i.e., the open-loop systems;