Optimal Robust Tuning for 1DoF PI/PID Control Unifying FOPDT/SOPDT Models

Alfaro, Víctor M.; Vilanova, Ramón

doi:10.3182/20120328-3-it-3014.00097

Cited by 22 publications

(25 citation statements)

References 17 publications

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“…There is no perfect alternative to the PID controller, at least at the bottom layer in the process industries. This was a clear conclusion at the end of the IFAC Conference on Advances in PID Control, held in Brescia (Italy) during 28-30 March, 2012. Although the PI controller has only two adjustable parameters, they are difficult to be tuned properly in real process.…”

Section: Introductionmentioning

confidence: 80%

“…The proposed method was compared with the uSORT 1 method of Alfaro and Vilanova [41] for P12. The parameters of the PI controller settings were taken from the paper of Alfaro and Vilanova [41] for M s =1.60.…”

Section: Comparison Of Proposed Methods With Robustness/performance Anmentioning

confidence: 99%

“…Alfaro and Vilanova [41] proposed the Unified Simple Optimal and Robust Tuning (uSORT 1 ) method. It is 1DoF PI/PID controller tuning method for the FOPDT and SOPDT process.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A unified approach for proportional-integral-derivative controller design for time delay processes

Shamsuzzoha

2014

Korean J. Chem. Eng.

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An analytical design method for PI/PID controller tuning is proposed for several types of processes with time delay. A single tuning formula gives enhanced disturbance rejection performance. The design method is based on the IMC approach, which has a single tuning parameter to adjust the performance and robustness of the controller. A simple tuning formula gives consistently better performance as compared to several well-known methods at the same degree of robustness for stable and integrating process. The performance of the unstable process has been compared with other recently published methods which also show significant improvement in the proposed method. Furthermore, the robustness of the controller is investigated by inserting a perturbation uncertainty in all parameters simultaneously, again showing comparable results with other methods. An analysis has been performed for the uncertainty margin in the different process parameters for the robust controller design. It gives the guidelines of the M s setting for the PI controller design based on the process parameters uncertainty. For the selection of the closed-loop time constant, (τ c ), a guideline is provided over a broad range of θ/τ ratios on the basis of the peak of maximum uncertainty (M s ). A comparison of the IAE has been conducted for the wide range of θ/τ ratio for the first order time delay process. The proposed method shows minimum IAE in compared to SIMC, while Lee et al. shows poor disturbance rejection in the lag dominant process. In the simulation study, the controllers were tuned to have the same degree of robustness by measuring the M s , to obtain a reasonable comparison.

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Section: Introductionmentioning

confidence: 80%

Section: Comparison Of Proposed Methods With Robustness/performance Anmentioning

confidence: 99%

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A unified approach for proportional-integral-derivative controller design for time delay processes

Shamsuzzoha

2014

Korean J. Chem. Eng.

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“…For the case of the bio-inspired methods, a minimum of 125 iteration where performed to ensure that the algorithms have opportunity to explore the complete solution space. In all cases, the initial value of the decision variables were set to be near the point given by the uSORT method with a maximum sensitivity of two [29]. The search space was restricted around ±20% of the uSORT point to avoid an unstable response during each iteration of the methods.…”

Section: Resultsmentioning

confidence: 99%

A comparison of bio-inspired optimization methodologies applied to the tuning of industrial controllers

Céspedes

Contreras

Cordero

et al. 2016

2016 IEEE 36th Central American and Panama Convention (CONCAPAN XXXVI)

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“…This is a clear example of one of the many advantages of using a multi-objective framework for controller tuning. The optimal parameters for the 2Dof-PID controller, for optimum tuning in disturbance rejection (J di ) and optimal servo control (J r ), are presented in in Table I, along with two other tunings: the ART 2 method [18] and the uSORT 2 [19], to compare the performance of the closed loop control. It is important to clarify that these two tuning are just the extreme points of the Pareto front, thanks to the ENNC method, the control engineer is able to select any closed-loop response between these two extremes, all of them equally optimal and robust.…”

Section: A Comparison Of Different Pid Tuning For a Benchmark Problemmentioning

confidence: 99%

Multi-objective optimal tuning of two degrees of freedom PID controllers using the ENNC method

Contreras-Leiva

Rivas

Rojas

et al. 2016

2016 20th International Conference on System Theory, Control and Computing (ICSTCC)

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Abstract-In this paper the Enhanced Normalized NormalConstrained method is applied to find the optimal tuning of second order PID controllers. This tuning takes into account both the servo and regulatory modes simultaneously, as well as a closed loop robustness criterion. The methodology is successfully applied to a high order linear plant and to a non linear continuous stirred tank reactor model, showing the effectiveness of the optimization methodology to solve control related problems. Also, the method is applied to a benchmark control system that takes into account three different sources of disturbances.

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Optimal Robust Tuning for 1DoF PI/PID Control Unifying FOPDT/SOPDT Models

Cited by 22 publications

References 17 publications

A unified approach for proportional-integral-derivative controller design for time delay processes

A unified approach for proportional-integral-derivative controller design for time delay processes

A comparison of bio-inspired optimization methodologies applied to the tuning of industrial controllers

Multi-objective optimal tuning of two degrees of freedom PID controllers using the ENNC method

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