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Special section on algorithms and applications of Iterative Feedback Tuning
Control Engineering Practice 11 (2003) 1021
Editorial
Special section on algorithms and applications of Iterative Feedback Tuning Iterative feedback tuning (IFT) is a flexible methodology for tuning controllers of arbitrary structure. The key feature is that closed-loop experimental data is used to directly compute a change of the controller parameters such that some performance objective is improved. Since no modeling step is required, the method is relatively simple to use. Thorough presentations of the method are provided in Hjalmarsson, Gevers, Gunnarsson, and Lequin (1998) and Hjalmarsson (2002). The fact that the system itself is used to generate the necessary information for improved closed-loop control has the advantage that the method is able to cope with . certain non-linearities (Hjalmarsson, 1998; Sjoberg & De Bruyne, 1999). In this special section, an interesting palette of applications of IFT are presented. In the first paper, Lequin and co-workers examine how IFT performs compared to classical PID tuning rules for single input/ single output systems. An elegant way of specifying the performance objective in a, for the user, simple way and which allows the algorithm itself to choose the most appropriate time-response is presented. Gunnarsson et al. show in the second paper that IFT can be used to tune PID type of controllers for multivariable systems. The procedure is illustrated on a robot joint control problem. Tuning of Internal Model Controllers (IMC) is considered by De Bruyne in the third paper. It is also pointed out that this opens up the way to tune Smith predictors with IFT. Feedforward suppression of narrow-band disturbances is the theme of the next paper. Meurers et al. use a frequency domain approach to active sound and vibration control which is tested on a laboratory set-up. A two-mass spring system with severe friction is studied by Hamamoto and co-workers in the following contribution. Both feedback and feedforward controllers are tuned using IFT equipped with a quasi-Newton update law. An innovative method which de-correlates the control error with lagged
0967-0661/03/$ - see front matter r 2003 Elsevier Ltd. All rights reserved. doi:10.1016/S0967-0661(03)00121-7
reference signal values is presented by Karimi and coworkers in the next paper. This approach requires less experimentation on the real system than standard IFT. . In the subsequent paper, Sjoberg et al. present a method which uses perturbations of the reference signal to compute signal sensitivities with respect to the controller parameters. This enables tuning of parameters in non-linear controllers. Using signal sensitivities to tune controllers has a long history (Hjalmarsson, 2002); in the last paper in the special section, Murray– Smith and co-workers present a time-domain convolution approach.
References Hjalmarsson, H. (1998). Control of nonlinear systems using Iterative Feedback Tuning. In Proceedings of the 1998 American control conference, Philadelphia (pp. 2083–2087). Hjalmarsson, H. (2002). Iterative feedback tuning—an overview. International Journal on Adaptive Control and Signal Processing, 16, 373–395. Hjalmarsson, H., Gevers, M., Gunnarsson, S., & Lequin, O. (1998). Iterative feedback tuning: Theory and applications. IEEE Control Systems Magazine, 18(4), 26–41. . Sjoberg, J., & De Bruyne, F. (1999). On a nonlinear controller tuning strategy. In 14th IFAC world congress, Vol. I, Beijing, People’s Republic of China (pp. 343–348).
Ha( kan Hjalmarsson Department of Signals, Sensors and Systems Royal Institute of Technology, Stockholm S-100 44, Sweden E-mail address: [email protected] Michel Gevers CESAME Universite! Catholique de Louvain 4 av. G Lemaitre, B-1348 Louvain-la-Neuve, Belgium E-mail address: [email protected]
Editorial
Special section on algorithms and applications of Iterative Feedback Tuning Iterative feedback tuning (IFT) is a flexible methodology for tuning controllers of arbitrary structure. The key feature is that closed-loop experimental data is used to directly compute a change of the controller parameters such that some performance objective is improved. Since no modeling step is required, the method is relatively simple to use. Thorough presentations of the method are provided in Hjalmarsson, Gevers, Gunnarsson, and Lequin (1998) and Hjalmarsson (2002). The fact that the system itself is used to generate the necessary information for improved closed-loop control has the advantage that the method is able to cope with . certain non-linearities (Hjalmarsson, 1998; Sjoberg & De Bruyne, 1999). In this special section, an interesting palette of applications of IFT are presented. In the first paper, Lequin and co-workers examine how IFT performs compared to classical PID tuning rules for single input/ single output systems. An elegant way of specifying the performance objective in a, for the user, simple way and which allows the algorithm itself to choose the most appropriate time-response is presented. Gunnarsson et al. show in the second paper that IFT can be used to tune PID type of controllers for multivariable systems. The procedure is illustrated on a robot joint control problem. Tuning of Internal Model Controllers (IMC) is considered by De Bruyne in the third paper. It is also pointed out that this opens up the way to tune Smith predictors with IFT. Feedforward suppression of narrow-band disturbances is the theme of the next paper. Meurers et al. use a frequency domain approach to active sound and vibration control which is tested on a laboratory set-up. A two-mass spring system with severe friction is studied by Hamamoto and co-workers in the following contribution. Both feedback and feedforward controllers are tuned using IFT equipped with a quasi-Newton update law. An innovative method which de-correlates the control error with lagged
0967-0661/03/$ - see front matter r 2003 Elsevier Ltd. All rights reserved. doi:10.1016/S0967-0661(03)00121-7
reference signal values is presented by Karimi and coworkers in the next paper. This approach requires less experimentation on the real system than standard IFT. . In the subsequent paper, Sjoberg et al. present a method which uses perturbations of the reference signal to compute signal sensitivities with respect to the controller parameters. This enables tuning of parameters in non-linear controllers. Using signal sensitivities to tune controllers has a long history (Hjalmarsson, 2002); in the last paper in the special section, Murray– Smith and co-workers present a time-domain convolution approach.
References Hjalmarsson, H. (1998). Control of nonlinear systems using Iterative Feedback Tuning. In Proceedings of the 1998 American control conference, Philadelphia (pp. 2083–2087). Hjalmarsson, H. (2002). Iterative feedback tuning—an overview. International Journal on Adaptive Control and Signal Processing, 16, 373–395. Hjalmarsson, H., Gevers, M., Gunnarsson, S., & Lequin, O. (1998). Iterative feedback tuning: Theory and applications. IEEE Control Systems Magazine, 18(4), 26–41. . Sjoberg, J., & De Bruyne, F. (1999). On a nonlinear controller tuning strategy. In 14th IFAC world congress, Vol. I, Beijing, People’s Republic of China (pp. 343–348).
Ha( kan Hjalmarsson Department of Signals, Sensors and Systems Royal Institute of Technology, Stockholm S-100 44, Sweden E-mail address: [email protected] Michel Gevers CESAME Universite! Catholique de Louvain 4 av. G Lemaitre, B-1348 Louvain-la-Neuve, Belgium E-mail address: [email protected]