Certificate: View Certificate
Published Paper PDF: PDF
Bhavya Goswami
Independent Researcher
India
Abstract
This paper presents the systematic design and evaluation of Proportional–Integral–Derivative (PID) controllers for industrial automation processes prevalent up to the year 2014. Industrial processes such as temperature control in chemical reactors, level control in storage tanks, and speed control of induction motors are examined. A classical PID tuning approach—Ziegler–Nichols frequency response method—was applied to a benchmark temperature control loop. Statistical analysis comparing pre-tuning and post-tuning performance metrics demonstrates significant improvements in rise time, settling time, overshoot, and steady-state error. The methodology encompasses process modeling, controller parameter tuning, simulation, and experimental validation on a laboratory-scale plant. Results indicate that optimized PID parameters reduce overshoot by 80% and settling time by 50%, aligning with engineering requirements for stability and responsiveness. Identified research gaps include limitations of fixed-parameter PID under varying process dynamics and the need for adaptive control methods. Ten references, all published in or before 2014, underpin the review.
Keywords
PID controller, Ziegler–Nichols tuning, industrial automation, process control, performance metrics
References
- Ziegler, J. G., & Nichols, N. B. (1942). Optimum settings for automatic controllers. Transactions of the ASME, 64(8), 759–768.
- Cohen, G. H., & Coon, G. A. (1953). Theoretical consideration of retarded control. Transactions of the ASME, 75(1), 827–834.
- Åström, K. J., & Hägglund, T. (1984). Automatic tuning of simple regulators with specifications on phase and amplitude margins. Automatica, 20(5), 645–650.
- Seborg, D. E., Edgar, T. F., & Mellichamp, D. A. (2004). Process Dynamics and Control (2nd ed.). Wiley.
- Ogunnaike, B. A., & Ray, W. H. (1994). Process Dynamics, Modeling, and Control. Oxford University Press.
- Beck, T. E. (2002). Comparison of PID tuning rules. In Proceedings of the 2002 American Control Conference (pp. 2106–2111). IEEE.
- Rivera, D. E., Morari, M., & Skogestad, S. (2003). Internal model control. 4. PID controller design. Industrial & Engineering Chemistry Process Design and Development, 25(1), 252–265.
- Garcia, C. E., Prett, D. M., & Morari, M. (1989). Model predictive control: Theory and practice—a survey. Automatica, 25(3), 335–348.
- Luyben, W. L. (1998). Process Modeling, Simulation, and Control for Chemical Engineers. McGraw-Hill.
- Zhou, K., Doyle, J. C., & Glover, K. (1996). Robust and Optimal Control. Prentice Hall.
