2DOF PI and PID Controllers Tuning

Vítečková, Miluše; Víteček, Antonín

doi:10.3182/20100607-3-cz-4010.00061

Cited by 33 publications

(19 citation statements)

References 2 publications

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“…Optimal controller parameters may be derived analytically by generalization of the approach applied in [27,28]. For the DIPDT model, it starts with a derivation of the closed loop transfer functions of 1DOF PID control, where…”

Section: Dof Pid Controller For the Dipdt Plant By The Qrdp Methodsmentioning

confidence: 99%

“…The multiple real dominant pole (MRDP) method represents one of the first analytical methods used for controller tuning [23]. In numerous later applications to the design of simple controllers, we could also mention P and PD controller design for time delayed integral systems in [18], or the design of PI and PID controllers in [27,28]. Whilst the above method directly gives both the dominant closed loop poles and the corresponding "optimal" controller parameters, in pole assignment control the choice of closed loop poles represents a crucial part of the controller tuning process.…”

Section: Introductionmentioning

confidence: 99%

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PID and filtered PID control design with application to a positional servo drive

Bélai¹,

Huba²,

Burn³

et al. 2019

Kybernetika

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Section: Dof Pid Controller For the Dipdt Plant By The Qrdp Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

PID and filtered PID control design with application to a positional servo drive

Bélai¹,

Huba²,

Burn³

et al. 2019

Kybernetika

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“…and by a filter Q n (equation 15) has been proposed in Huba. 55 It is based on a tuning derived for an unfiltered time delayed loop to guarantee a triple real dominant pole (TRDP) s o of the characteristic quasi-polynomial P(s) 56 satisfying P(s o ) = 0, _ P(s o ) = 0 and € P(s o ) = 0, when the corresponding optimal PI controller parameters K co and T io are…”

Section: -Dof Fpi Controller Tuningmentioning

confidence: 99%

Limits of a simplified controller design based on integral plus dead time models

Huba

Bélai

2018

Proceedings of the Institution of Mechanical Engineers, Part I:

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This article presents design and evaluation of filtered proportional-integral controllers and filtered Smith predictorinspired constrained dead time compensators. Both are based on the integral plus dead time and on the first-order time delayed plant models. They are compared as for tuning simplicity, robustness and noise attenuation. Such a comparison, which presents a robustness test regarding the importance of the internal plant feedback approximation, may be carried out by performance measures built on deviations of the input and output transient responses from their ideal shapes. When combined with integral of absolute error measures of both solution types with the disturbance responses set as nearly equivalent, we can see that the filtered Smith predictor setpoint responses may be significantly faster than the filtered proportional-integral controller responses, more robust and, using higher-order filters, also sufficiently smooth. Furthermore, tuning of the possibly higher-order filters for filtered Smith predictor is simpler. Its overall design is more transparent and straightforward with respect to the control constraints, where the filtered Smith predictor requires some additional anti-windup measures.

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“…Then, in Reference [56], a derivation of higher-order PID controllers by generalising the Skogestad Internal Model Control (SIMC) method [8] for analytical model-based controller tuning was proposed. In Reference [59], robust and simple analytical 2-DOF PI/PID controller tuning rules based on the multiple dominant pole method (MDPM) were proposed. The method enables calculation of controller parameters while maintaining non-oscillatory closed-loop responses without overshoots.…”

Section: Introductionmentioning

confidence: 99%

Parametric and Nonparametric PID Controller Tuning Method for Integrating Processes Based on Magnitude Optimum

2020

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Integrating systems are frequently encountered in power plants, paper-production plants, storage tanks, distillation columns, chemical reactors, and the oil industry. Due to the open-loop instability that leads to an unbounded output from a bounded input, the efficient control of integrating systems remains a challenging task. Many researchers have addressed the control of integrating processes: Some solutions are based on a single closed-loop controller, while others employ more complex control structures. However, it is difficult to find one solution requiring only a simple tuning procedure for the process. This is the advantage of the magnitude optimum multiple integration (MOMI) tuning method. In this paper, we propose an extension of the MOMI tuning method for integrating processes, controlled with a two-degrees-of-freedom (2-DOF) proportional–integral–derivative (PID) controller. This extension allows for calculations of the controller parameters from either time domain measurements or from a process transfer function of an arbitrary order with a time-delay, when both approaches are exactly equivalent. The user has the option to emphasise disturbance-rejection or tracking with the reference weighting factor b or apply two different reference filters for the best overall response. The proposed extension was also compared to other tuning methods for the control of integrating processes and tested on a charge-amplifier drift-compensation system. All closed-loop responses were relatively fast and stable, all in accordance with the magnitude optimum criteria.

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2DOF PI and PID Controllers Tuning

Cited by 33 publications

References 2 publications

PID and filtered PID control design with application to a positional servo drive

PID and filtered PID control design with application to a positional servo drive

Limits of a simplified controller design based on integral plus dead time models

Parametric and Nonparametric PID Controller Tuning Method for Integrating Processes Based on Magnitude Optimum

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