铣削过程在线辨识与极点配置自适应控制

 研究了铣削加工过程的建模、参数在线辨识及自适应控制问题，为铣削过程建立了二阶离散传递函数模型，提出了一种修正的带遗忘因子递推最小二乘参数辨识算法，从而解决了普通递推最小二乘辨识算法中由于递推计算协方差矩阵衰退或膨胀引起辨识结果失真的问题，采用极点配置设计原理，为铣削过程推导了自适应控制的控制律。仿真和实验表明，修正的最小二乘辨识算法和极点配置自适应控制律是正确和可靠的，自适应控制器可获得所需的响应性能。

ON-LINE IDENTIFICATION AND POLE ASSIGNMENT ADAPTIVE CONTROL FOR MILLING PROCESS

This paper investigates modeling, on line parameter identification and adaptive control for the milling process. A second order discrete time transfer function is derived for the milling process. Based on the ordinary recursive least squares, a modified identification algorithm is suggested so as to eliminate the parameter distortion caused by the degeneration or expansion of the covariance matrix. The adaptive control law for the milling process is developed using pole assignment principle according to the desired objective transfer function of the closed loop system including the adaptive controller and the process. A PC/DSP based adaptive control system is built up to verify the algorithms of the adaptive controller. The modified recursive least squares and the pole assignment adaptive control law are plugged into a real time software platform, Intelligent Machining Modules(IMM), as plug in modules(PIMs) written in ANSI C codes. The simulation and experiment have demonstrated that the algorithms for identification and adaptive control are stable, reliable and robust. The milling process controlled by the adaptive controller behaves with the desired performance.