A New Approach to Closed-Loop Autotuning for Proportional−Integral−Derivative Controllers

Luo, Rongfu; Qin, S. Joe; Chen, Dapang

doi:10.1021/ie970675j

Cited by 9 publications

(6 citation statements)

References 6 publications

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“…Two of the most relevant techniques are relay feedback (Hagglund and Astrom, 1985), and set point relay (Luo et al, 1998). Some recent findings in this area are iterative tuning with cost minimization (Akerblad et al, 2000) and Auto-tuning of PID using Loop-shaping ideas (Gaikwad et al, 1999).…”

Section: Auto-tuningmentioning

confidence: 99%

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Design and implementation of a fuzzy supervisor for on-line compensation of nonlinearities: An instability avoidance module

Sanjuán

Kandel

Smith

2006

Engineering Applications of Artificial Intelligence

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Section: Auto-tuningmentioning

confidence: 99%

“…It is common practice in process engineering to identify self-regulated processes using a First-OrderPlus-Dead Time (FOPDT) model at the operating condition for tuning purposes (Marlin, 2000;Smith and Corripio, 1997;Shinskey, 1996). Recent developments in PID Auto-tuning (Luo et al, 1998) …”

Section: Stability Issues Of Pid Control Loopsmentioning

confidence: 99%

Design and implementation of a fuzzy supervisor for on-line compensation of nonlinearities: An instability avoidance module

Sanjuán

Kandel

Smith

2006

Engineering Applications of Artificial Intelligence

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“…For example, modifications of the popular relay auto-tuning method [204] and [7] have been reported (e.g., [139]) including extensions to multi-loop control [83], [167] and [240]. Refinements to the ZN rules and tuning relations for unstable processes have been published [142], [8] and [9].…”

Section: Controller Tuning and Adaptive Controlmentioning

confidence: 99%

A Perspective on Advanced Strategies for Process Control (Revisited)

Seborg

1999

Advances in Control

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Summary. Th is paper provides a personal perspective on the current status of advanced process control. First, process control strategies are classified according to the extent to which they have been applied in industry. Then important new developments in information technology and plant automation are summarized. Prominent advanced process control methods are critiqued with emphasis placed on key issues and unresolved research problems. Finally, recent developments in an important related field, process monitoring, are reviewed.

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“…Autotuning algorithms (Wang and Shao, 1999;Friman and Waller, 1997;Luo and Chen, 1998) and trial-and-error tuning by plant personnel are also commonly employed methods for tuning PID controllers.…”

mentioning

confidence: 99%

“…Other PID design methods include frequency response and root locus, classical approaches to tuning parameter determination (Franklin et al, 1991;Smith and Corripio, 1985). Autotuning algorithms (Wang and Shao, 1999;Friman and Waller, 1997;Luo and Chen, 1998) and trial-and-error tuning by plant personnel are also commonly employed methods for tuning PID controllers.…”

mentioning

confidence: 99%

A Simplified Numerical Approach to Feedback Controller Design

Bechtel¹

2004

Can J Chem Eng

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T here exist several well-established techniques for feedback control design for dynamic systems. The technique employed depends on the structure of the controller, i.e., conventional proportionalintegral-derivative (PID), linear or nonlinear state feedback, and so on.For the control of industrial chemical processes, PID control is widely used, accounting for some 95% of all control loops (Wang and Shao, 1999). Therefore, it is not surprising that much attention has been paid to tuning this type of controller. Luyben (2001) presents a comparison of PID tuning methods for processes possessing varying degrees of dead-time. One of these methods is the classic Ziegler-Nichols tuning method, which determines the controller gain, integral time, and derivative time by using either the system ultimate gain or process reaction curve (Ziegler and Nichols, 1942;Dutton et al., 1997).Other PID design methods include frequency response and root locus, classical approaches to tuning parameter determination (Franklin et al., 1991;Smith and Corripio, 1985). Autotuning algorithms (Wang and Shao, 1999;Friman and Waller, 1997;Luo and Chen, 1998) and trial-and-error tuning by plant personnel are also commonly employed methods for tuning PID controllers.The Ziegler-Nichols process reaction curve, autotuning, and trialand-error approaches, while useful in many circumstances, have the potential disadvantage of introducing transients to the process, risking process upsets and unstable response. Closed-loop autotuning algorithms help to circumvent these potential problems. However, an autotuning feature is not available on many industrial PID controllers, so it is not always a viable alternative.Approaches to feedback control design that are based on state-space methods have gained popularity for chemical process control (Ray, 1989). One class of linear optimal control problem is the linear regulator, in which optimal, time-varying gains are computed which minimize a quadratic performance index. Ray (1989), Sage et al. (1977), and Kirk (1970) discuss solutions to the linear regulator problem, including solution via backward integration of the Riccati equation and by direct numerical techniques that require fi rst-and sometimes second-derivative information. For infi nite time problems, such as the continuous control of a chemical process, the time-varying gains become constant, resulting in constant gain proportional controllers. Integral control may be implemented as well, in order to eliminate steady-state offset (Franklin et al., 1991). Ray (1989) discusses application of optimal control theory to nonlinear systems and associated numerical solution techniques. Non-optimal state-space methods (Franklin et al., 1991) utilize pole placement or comparison with prototype response models such as Bessel functions, Integral of Time Multiplied by Absolute Value of Error (ITAE), or Integral of the Square of the Error (ISE) criteria in order to select appropriate controller gains. * Author to whom correspondence may be addressed. E-mail address: ...

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A New Approach to Closed-Loop Autotuning for Proportional−Integral−Derivative Controllers

Cited by 9 publications

References 6 publications

Design and implementation of a fuzzy supervisor for on-line compensation of nonlinearities: An instability avoidance module

Design and implementation of a fuzzy supervisor for on-line compensation of nonlinearities: An instability avoidance module

A Perspective on Advanced Strategies for Process Control (Revisited)

A Simplified Numerical Approach to Feedback Controller Design

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