https://instruct.uwo.ca/engin-sc/391b/MFILES/es512_420/PIDtuning.pdf

Simple analytic rules for model reduction and PID controller tuning

http://www.cpdee.ufmg.br/~palhares/Revisiting_Ziegler_Nichols_step_response_method_for_PID.pdf?origin=publication_detail

Revisiting the Ziegler-Nichols step response method for PID control

The paper first briefly reviews the analytical procedures for obtaining optimum PID controller settings for minimisation of time weighted integral performance criteria. The approach is then used to obtain formulae for setting the controller parameters for a first-order plus dead time plant model which is a common approximation used in the process industries. These results are further extended to obtain two procedures, which can be used with the relay autotuning approach, to find the required controller parameters for optimisation of the integral of time error squared criterion. Good results have been obtained when these criteria are used with other plant models.

Automatic tuning of optimum PID controllers

Preface Introduction The Hermite-Biehler Theorem and Its Generalization PI Stabilization of Delay-Free Linear Time-Invariant Systems PID Stabilization of Delay-Free Linear Time-Invariant Systems Preliminary Results for Analyzing Systems with Time Delay Stabilization of Time-Delay Systems Using a Constant Gain Feedback Controller PI Stabilization of First-Order Systems with Time Delay PID Stabilization of First-Order Systems with Time Delay Control System Design Using the PID Controller Analysis of Some PID Tuning Techniques PID Stabilization of Arbitrary Linear Time-Invariant Systems with Time Delay Algorithms for Real and Complex PID Stabilization A Proof of Lemmas 8.3, 8.4, and 8.5 B Proof of Lemmas 8.7 and 8.9 C Detailed Analysis of Example 11.4 References Index

PID Controllers for Time Delay Systems

The performance and robustness of well-known PID formulas for process with deadtime to time constant ratio between 0.1 and 1 are discussed in this paper. The Ziegler-Nichols, Cohen-Coon, and tuning formulas that optimize for load disturbance response (integral absolute error, integral squared error, and integral time-weighted absolute error) give gain margins of about 1.5. The phase margins increase from about 30 to 60/spl deg/ as the process deadtime to time constant ratio increases from 0.1 to 1. Tuning formulas that optimize setpoint response give gain margins of about two and phase margins of about 65/spl deg/. These formulas mostly make use of the proportional-integral derivative (PID) controller zeros to cancel the process poles. Approximate analytical formulas to compute gain and phase margins of PID control systems are also derived in this paper to facilitate online computation which would be particularly useful for implementing adaptive control.

Performance and gain and phase margins of well-known PID tuning formulas

1. Introduction. 2. Mathematical Tools for Control Systems Analysis. 3. First-Order Dynamic Systems. 4. Higher-Order Dynamic Systems. 5. Basic Components of Control Systems. 6. Design of Single Loop Feedback Control Systems. 7. Tuning of Feedback Controllers. 8. Root Locus and Frequency Response Techniques. 9. Cascade Control. 10. Ratio, Override and Selective Control. 11. Feedforward Control. 12. Multivariable Process Control. 13. Dynamic Simulation of Control Systems. Appendix A: Instrumentation Symbols and Labels. Appendix B: Design Case Studies. Appendix C: Sensors, Transmitters, and Control Valves. Appendix D: Tuning Case Studies. Appendxi E: Operating Case Studies. Index.

Principles and Practice of Automatic Process Control

La obra es una referencia indispensable en la ingenieria de procesos. Esta nueva edicion presenta cambios sustanciales con respecto a la edicion anterior, como la reorganizacion de los contenidos y la eliminacion de material obsoleto, y temas nuevos, como la simulacion dinamica, pero conserva su enfasis original en la teoria de control y su aplicacion practica en la industria. Por esta razon, uno de los cambios mas importantes es la actualizacion de ejemplos y problemas, asi como de los estudios de caso. El diseno de un sistema de control implica identificar los objetivos de control, la seleccion de los parametros de medicion y operacion del proceso, asi como la determinacion de los lazos y la identificacion de los algoritmos que brinden el control apropiado. Carlos A. Smith es Profesor del Departamento de Ingenieria Quimica de la University of South Florida. Armando B. Corripio es Profesor del Departamento de Ingenieria Quimica de la Lousiana State University.

Armando B. Corripio

Papers

Principles and Practice of Automatic Process Control

Control automático de procesos: teoría y práctica