Research on Adaptive Identification Systems to Estimate Dynamic Behaviors of Moving Objects

在本研究中，我们推导出自适应参数调整律来估计和控制非线性系统的动态行为。我们用一个满足黎卡提方程的动态误差系统代替了Lurie方程，并用σ修正的类参数调节律证明了误差系统的有界性。利用所提出的模糊自适应辨识器设计了具有未知输入非线性的未知稳定对象的模糊自适应辨识器，并针对具有两个输入和两个输出的球板装置设计了模糊辨识器和控制器。球板系统是由TEquipment Inc.生产的教育工具包，它由一个在其中心枢转的板组成，使板的斜率可以在两个垂直方向上操作，并具有用于测量球位置的智能视觉系统。首先，给出了球-板系统的一个非线性模型，称为由模糊基函数展开的模糊逼近器。得到的模糊模型包含系统参数和由模糊基函数组成的回归信号的乘积。其次，为了估计模糊模型中的未知系统参数，将对象参数的线性辨识器添加到输入非线性的模糊辨识器中。最后，通过仿真和实验研究了该模糊辨识器的性能。

In this research, we derived the adaptive parameter adjustment law to estimate and control of dynamic behavior of nonlinear systems. We used a dynamic error system which satisfied a Riccati equation instead of the Lurie' equations, and showed the boundedness of the error system using σ-modification-like parameter adjustment law. Using the proposed We desinged the fuzzy adaptive identifier for unknown stable plants with unknown input nonlinearities, and designed a fuzzy identifier and a controller for the ball-plate apparatus which has two inputs and two outputs. The ball-plate system is the educational kit produced by Tequipment Inc., which consists of a plate pivoted at its center such that the slope of the plate can be manipulated in two perpendicular directions and which has the intelligent vision system for measurement of a ball position. First, a nonlinear model, called the fuzzy approximator expanded by the fuzzy basis functions, of the ball-plate system is given. The obtained fuzzy model contains the product of the system parameters and regressor signals consist of the fuzzy basis functions. Next, to estimate the unknown system parameters in the fuzzy model, the linear identifier for plant parameters is added to the fuzzy identifier for input nonlinearities. Finally, the performance of the proposed fuzzy identifier is investigated by the MATLAB simulation and the experiment.