闭环系统的虚拟参考反馈校正控制及迭代最小辨识

在线性框架下研究基于输入输出观测数据对未知系统模型中两反馈控制器的设计问题. 采用虚拟参考反馈校正控制直接设计控制器，无需系统建模过程. 在构造代价函数时，同时考虑闭环传函和灵敏度的模型-匹配问题. 针对模型匹配过程，分别设计虚拟输入和扰动；推导用于观测数据预处理的滤波器. 在设计控制器前，利用概率统计法对控制器进行检验以保证闭环系统的稳定性. 针对控制设计中的参数优化，利用数值优化理论分析迭代最小二乘辨识算法所生成的迭代序列与全局最优值间的逼近式，以此式作为评价收敛性和收敛速度的依据. 最后用仿真算例验证方法的有效性.

Virtual reference feedback tuning control and iterative minimization identification in closed-loop system

In this paper, we discuss the problem of designing two feedback controllers for an unknown plant based on input-output measurements in a linear setting. The virtual reference feedback tuning is used to design controller. No model identification of the plant is needed. When constructing the cost function, we consider model-matching problems between closed loop transfer function and sensitivity function simultaneously. In model-matching procedures, we analysis how to design the virtual input and disturb respectively and derive a filter expression used to filter measurement data. A controller validation test aiming at attain the closed-loop stability before the designed controller is applied to the plant. To the parameter optimization problem, we analysis the iterative sequence generated by the iterative least square identification algorithm. Furthermore we derive the approximation relation expression between the iterative sequence and global optimum value. Based on this approximation relation expression, we evaluate the algorithm's convergence property and velocity. Finally the simulation example results confirm the theoretical results.