ONLINE PROCESS IDENTIFICATION USING THE LAGUERRE SERIES FOR AUTOMATICTUNING OF THE PROPORTIONAL-INTEGRAL-DERIVATIVE CONTROLLER

A new on-line identification method based on the approximation of clos ed-loop response is proposed to tackle the shortcomings of previous au totuning methods using a proportional controller as a test signal gene rator. That is, for both the overdamped and the underdamped closed-loo p response in the identification step, the proposed method can easily estimate the second-order plus time delay model only with the measurem ents of the transient. From the orthonormal property of the Laguerre s eries, the closed-loop response in the identification step is approxim ated by a simple least-squares technique effectively, and then a high- order process transfer function is estimated from it. Finally, a simpl e model reduction method is used to reduce the high-order process tran sfer function to a second-order plus time delay model via the least-sq uares technique in the frequency domain. The proposed method does not need any numerical technique such as root-finding or iterative optimiz ation Since it uses all the measurements of transient response instead of several dominant data points such as peak or valley values, the ro bustness to the measurement noise is greatly enhanced. From simulation results and comparisons with previous works, we can recognize that it provides more accurate models and better control performances for var ious process dynamics. In experimental study, it can be noted that it is also very effective in identification and control of real processes .