Modeling and control of Wiener-type processes

We develop a simple relay feedback method to identify Wiener-type nonlinear processes. It separates the identification problem of the nonlinear static function from that of the linear dynamic subsystem to simplify the identification procedure significantly. Owing to the separation, the unmeasurable output of the linear dynamic subsystem can be obtained in a straightforward manner. Then, determining the model structure of the nonlinear static function becomes very simple and the estimates are robust to additive output noises. We can identify the whole activated region of the nonlinear static function as well as the ultimate information of the linear dynamic subsystem from only one relay feedback test. More information on the linear dynamic subsystem can be estimated by well-established linear system identification methods from additional tests. We use a nonlinear control strategy to compensate the nonlinear dynamics of the Wiener process so that the design parameters can be determined by usual tuning rules developed for linear processes and a high control performance can be achievable as in linear processes.

[1]  Michel Verhaegen,et al.  Continuous-time identification of SISO systems using Laguerre functions , 1999, IEEE Trans. Signal Process..

[2]  B. Cheng,et al.  Analysis and parameter estimation of bilinear systems via block-pulse functions , 1982 .

[3]  William L. Luyben,et al.  Nonlinear auto-tune identification , 1994 .

[4]  Dale E. Seborg,et al.  Application of a general multi-model approach for identification of highly nonlinear processes-a case study , 1993 .

[5]  Tore Hägglund,et al.  Automatic tuning of simple regulators with specifications on phase and amplitude margins , 1984, Autom..

[6]  Su Whan Sung,et al.  Prediction Error Identification Method for Continuous-Time Processes with Time Delay , 2001 .

[7]  Su Whan Sung,et al.  pH control using an identification reactor , 1995 .

[8]  Su Whan Sung,et al.  New Process Identification Method for Automatic Design of PID Controllers , 1998, Autom..

[9]  S. Sagara,et al.  Recursive identification of transfer function matrix in continuous systems via linear integral filter , 1989 .

[10]  Su Whan Sung,et al.  Continuous-Time Subspace System Identification Method , 2001 .

[11]  J. G. Ziegler,et al.  Optimum Settings for Automatic Controllers , 1942, Journal of Fluids Engineering.

[12]  E. Eitelberg Continuous-time system representation with exact macro-difference expressions , 1988 .

[13]  Lennart Ljung,et al.  System Identification: Theory for the User , 1987 .

[14]  Michel Verhaegen,et al.  Stochastic theory of continuous-time state-space identification , 1999, IEEE Trans. Signal Process..

[15]  Hsiao-Ping Huang,et al.  Identification of Wiener Model Using Relay Feedback Test , 1998 .

[16]  W. R. Cluett,et al.  Identification of Wiener-type nonlinear systems in a noisy environment , 1997 .

[17]  Sunwon Park,et al.  Optimal PID Controller Tuning Method for Single-Input-Single-Output Process , 2002 .

[18]  In-Beum Lee,et al.  Modified relay feedback method , 1995 .

[19]  W. R. Cluett,et al.  A new approach to the identification of pH processes based on the Wiener model , 1995 .