论文标题
通过未知物理参数参数化的系统的指数稳定自适应观察
Exponentially Stable Adaptive Observation for Systems Parameterized by Unknown Physical Parameters
论文作者
论文摘要
对于通过未知物理参数参数化的线性时间存在系统，提出了设计指数稳定的自适应观察者的方法。与现有的自适应解决方案不同，系统空间矩阵A，B不限于以观察者规范形式表示以实现观察者。相反，使用原始系统描述，因此获得了原始的状态向量。适用于该方法的系统类别是通过与：（i）控制信号和所有系统轨迹的界限相关的三个假设，（ii）从分子和deminator colynomials的系统输入/输出传输功能以及（iii）系统状态的完全可观察到系统状态的a和b物理参数的可识别性。如果它们被满足并且回归剂是有限的令人兴奋的，则根据已知的GPEBO和DREM程序，提出的自适应观察者确保了系统参数和状态估计对其真实值的指数收敛。已经提供了稳定性和收敛性的详细分析以及拟验证开发理论的仿真结果。
The method to design exponentially stable adaptive observers is proposed for linear time-invariant systems parameterized by unknown physical parameters. Unlike existing adaptive solutions, the system state-space matrices A, B are not restricted to be represented in the observer canonical form to implement the observer. The original system description is used instead, and, consequently, the original state vector is obtained. The class of systems for which the method is applicable is identified via three assumptions related to: (i) the boundedness of a control signal and all system trajectories, (ii) the identifiability of the physical parameters of A and B from the numerator and denominator polynomials of a system input/output transfer function and (iii) the complete observability of system states. In case they are met and the regressor is finitely exciting, the proposed adaptive observer, which is based on the known GPEBO and DREM procedures, ensures exponential convergence of both system parameters and states estimates to their true values. Detailed analysis for stability and convergence has been provided along with simulation results to validate the developed theory.
