A model-free direct synthesis method for PI/PID controller design based on disturbance rejection

Jeng, Jyh‐Cheng

doi:10.1016/j.chemolab.2015.08.004

Cited by 19 publications

(8 citation statements)

References 24 publications

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“…Some other authors used the PID controller for the regulation purpose in similar cases [49][50][51]. The non-linear ANN unit and the condenser pressure unit algorithm structure will be presented in detail below.…”

Section: Lrvp Simulation Modelmentioning

confidence: 99%

Energy efficiency analysis of steam ejector and electric vacuum pump for a turbine condenser air extraction system based on supervised machine learning modelling

et al. 2016

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Section: Lrvp Simulation Modelmentioning

confidence: 99%

Energy efficiency analysis of steam ejector and electric vacuum pump for a turbine condenser air extraction system based on supervised machine learning modelling

et al. 2016

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“…Several tuning methods for IP have been developed so far [17,18]. They can be classified according to models of integrating systems, i.e., tuning methods for integrating systems with time-delay [7,[19][20][21][22][23][24][25][26][27][28], for first-order integrating systems with time-delay [18,, for higher-order integrating systems with time-delay [52], and nonparametric tuning methods for integrating systems [53][54][55][56].…”

Section: Introductionmentioning

confidence: 99%

“…Nonparametric controller-tuning methods are model-free (data-based), i.e., they directly exploit a set of closed-or open-loop-process data without requiring the use of a process model. Jeng [53] proposed a PI/PID controller method that was based on the direct synthesis approach and specification of the desired closed-loop transfer function for disturbances. The set-point response can be independently improved by using set-point weighting in the PID controllers.…”

Section: Introductionmentioning

confidence: 99%

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

2020

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Integrating systems are frequently encountered in the oil industry (oil–water–gas separators, distillation columns), power plants, paper-production plants, polymerisation processes, and in storage tanks. Due to the non-self-regulating character of the processes, any disturbance can cause a drift of the process output signal. Therefore, efficient closed-loop control of such processes is required. There are many PI and PID controller tuning methods for integrating processes. However, it is hard to find one requiring only a simple tuning procedure on the process, while the tuning method is based either on time-domain measurements or on a process transfer function of arbitrary order, which are the advantages of the magnitude optimum multiple integration (MOMI) tuning method. In this paper, we propose the extension of the MOMI tuning method to integrating processes. Besides the mentioned advantages, the extension provides efficient closed-loop control, while PI controller parameters calculation is still based on simple algebraic expressions, making it suitable for less-demanding hardware, like simpler programmable logic controllers (PLC). Additionally, the proposed method incorporates reference weighting factor b that allows users to emphasize either the disturbance-rejection or reference-following response. The proposed extension of the MOMI method (time-domain approach) was also tested on a charge-amplifier drift-compensation system, a laboratory hydraulic plant, on an industrial autoclave, and on a solid-oxide fuel-cell temperature control. All closed-loop responses were relatively stable and fast, all in accordance with the magnitude optimum criteria.

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“…Numerous IP tuning methods have been proposed so far [9,34]. These techniques can be classified according to their IP model structure, i.e., tuning methods for ITD [20,, for IFOTD [8,32,34,, for higher-order IPs with time-delay [108][109][110][111][112][113][114], and nonparametric tuning methods for IPs [1,[115][116][117].…”

Section: Introductionmentioning

confidence: 99%

“…This is an attractive approach for alleviating the drawbacks of process-model mismatches. A PI/PID controller tuning method that enables specification of the desired closed-loop transfer function for disturbance-rejection, while tracking, using PID controllers, can be independently improved with set-point weighting, was proposed in Reference [115]. A tuning method for PI and PID controllers, based on an extended relay feedback procedure, was proposed in Reference [117].…”

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.

show abstract

A model-free direct synthesis method for PI/PID controller design based on disturbance rejection

Cited by 19 publications

References 24 publications

Energy efficiency analysis of steam ejector and electric vacuum pump for a turbine condenser air extraction system based on supervised machine learning modelling

Energy efficiency analysis of steam ejector and electric vacuum pump for a turbine condenser air extraction system based on supervised machine learning modelling

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

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

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