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Practical Design of PID-type Controllers with Constraints

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2016 ASEE Annual Conference & Exposition


New Orleans, Louisiana

Publication Date

June 26, 2016

Start Date

June 26, 2016

End Date

June 29, 2016





Conference Session

Robotics, Automation, and Product Development

Tagged Division

Engineering Technology

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Paper Authors


Vassilios Tzouanas University of Houston, Downtown

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Vassilios Tzouanas is an Associate Professor of Computer Science and Engineering Technology at the University of Houston – Downtown, in Houston, Texas. He also serves as assistant department chairman. He received all his degrees in chemical engineering and obtained his Ph.D. from Lehigh University. His area of specialization is process modeling, simulation and control. He has worked in the industry for 19 years where he held technical and management positions with major operating companies as well as process control technology development companies. Since 2010, he has been with UHD where he teaches university courses in process control, modeling and simulation, process design and operation, applied thermodynamics and heat transfer, and numerical methods. Dr. Tzouanas' research interests include process modeling, simulation and design, process control, and renewable energy systems. Dr. Tzouanas is an ABET Program Evaluator (PEV) for Engineering and Engineering Technology programs. He is also member of AIChE and ASEE.

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Steely Earl Varon Falar University of Houston, Downtown

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Mr. Steely Falar is a senior student in the Controls and Instrumentation Engineering Technology Program at the University of Houston-Downtown. He holds an AAS degree in Controls and Instrumentation from Houston Community College. His interests include process control, programmable logic controllers, and design of effective human-machine interfaces.

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Practical Design of PID-type Controllers with Constraints

The proportional-integral-derivative (PID) controller has been extensively used in the process industries and is taught in most undergraduate engineering and engineering technology programs. Various PID design methods have been proposed over the years such as the famous Ziegler-Nichols method [1], the Internal Model Control (IMC) method [2], and many variations of it.

Given a process model, these methods estimate values for the PID tuning parameters: proportional gain, integral time, and derivative time. However, most of these methods include a tunable parameter, for instance the filter time constant in the case of the IMC method that the user must tune. In addition, manufacturers of control systems include PID controllers with additional tunable parameters for setpoint weighting and derivative filtering. Furthermore, none of these techniques considers process constraints in the PID design. However, from a practical viewpoint, process and control element constraints must be accounted for.

A methodology based on co-simulation has been developed to tune PID controllers subject to controlled variable as well as manipulated variable (size and rate) constraints while a performance criterion is optimized [3].

This paper extends the methodology of [3] to determine the “tunable” parameters of other PID design methods while process and equipment constraints are satisfied. Estimation of the IMC filter time constant, setpoint weighting, and derivative filter will be considered. Simulation and experimental results demonstrate the practicality of the new PID design method.


[1] Ziegler, J.G & Nichols, N.B. (1942). Optimum settings for automatic controllers. Trans. ASME 64, 759–768.

[2] Rivera, D.E., Morari, M & Skogestad, S. (1986). Internal model control 4.PID controller design. Industrial & Engineering Chemistry Process Design and Development, 25, 252–265.

[3] Tzouanas, C. & Tzouanas, V. (2013). Optimal Tuning of PID Controllers subject to Process Constraints. International Journal of Modern Engineering, 14(1), 70-80.

Tzouanas, V., & Falar, S. E. V. (2016, June), Practical Design of PID-type Controllers with Constraints Paper presented at 2016 ASEE Annual Conference & Exposition, New Orleans, Louisiana. 10.18260/p.25922

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