Impact of the Sampling Period on the Design of Digital PID Controllers

Author:

Tsamatsoulis Dimitris1

Affiliation:

1. Halyps Building Materials S.A. 17th klm Nat. Road Athens – Korinth, Aspropyrgos, Greece

Abstract

The impact of the sampling period on the parameterization of a digital PID controller in the frequency domain is attempted using three different digital approximations of the integral action. The controller is implemented in the industrial process of regulation of the cement sulphates in the cement mill outlet. The maximum sensitivity, Ms, has been utilized as a main robustness criterion. For the same Ms, proportional and differential gain, a rise of the sampling period leads to a decrease of the integral gain ki for all the three approximations. For the same sampling period, the function between proportional and integral gain differs for the three approximations studied. If the design satisfies two criteria simultaneously, maximum sensitivity and phase margin in the current study, then the permissible PID gains zone becomes narrower.

Publisher

North Atlantic University Union (NAUN)

Subject

Pharmacology (medical),Complementary and alternative medicine,Pharmaceutical Science

Reference9 articles.

1. K. Astrom and T. Hagglund, Advanced PID Control, Instrumentation, Systems and Automatic Society: Research Triangle Park, 2006, pp. 1, pp 414-423.

2. R.E.Kalman, “Nonlinear Aspects of Sampled Data Control Systems,” Proc. Of the Symposium on Non-linear Circuit Analysis, vol.VI, 1956, pp.273-313.

3. J. M. Madsen, L. Shieh and S. Guo, “State-space Digital PID Controller Design for Multivariable Analog Systems with Multiple Time Delays”, Asian Journal of Control, vol. 8, pp. 161-173, June 2006.

4. D. E. Seborg, T. F. Edgar and D.A. Mellichamp, Process Dynamics and Control, 2nd ed., Jon Wiley & Suns, 2004, pp. 461-468.

5. S. Das, I. Pan, K. Halder, S. Das and A. Gupta, “LQR Based Improved Discrete PID Controller Design via Optimum Selection of Weighting Matrices Using Fractional Order Integral Performance Index”, Applied Mathematical Modelling, vol. 37, pp. 4253–4268, 15 March 2013.

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