Novel proportional–integral–derivative controller with second order filter for integrating processes

Kumar, M. Praveen; Manimozhi, M.

doi:10.1002/apj.2195

Cited by 26 publications

(34 citation statements)

References 21 publications

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“…To reduce overshoots, a second-order reference filter is employed. Similar tuning rules were proposed by the same authors in Reference [106], where overshoots are reduced by cancelling some controller zeros and using fourth-order reference filtering. In Reference [97], analytical tuning rules for a 2-DOF PID controller, where overall optimal closed-loop response is obtained via two-step tuning of the closed-loop transfer function, were proposed.…”

Section: Introductionmentioning

confidence: 89%

“…The proposed tuning method for the PID f2 and PID fh controllers was compared to five other methods [18,77,97,103,106]. The first method is Ali and Majhi's method [77] (hereafter denoted as Ali-Majhi) for 1-DOF PID controllers.…”

Section: Comparisons With Other Methodsmentioning

confidence: 99%

“…The denominator of the Filter (30) is chosen to cancel the controller zeros in the closed-loop transfer Function (28), similar to the approach proposed by Medarametla and Manimozhi [106]. The numerator of the filter (parameters b F1 and b F2 ) is then calculated by equating the first two characteristic areas (A 0 and A 1 ) of the closed-loop transfer Function (28) (using Expression (8) with G CL instead of G P1 in the Expression (7)) with the equivalent areas of the desired closed-loop transfer function G CL1 when using the PD Controller (29).…”

Section: The Second-order Filtermentioning

confidence: 99%

“…Note that most tunings methods for IFOTD can also be applied to other types of IPs if the process can be modelled by the IFOTD model [8,68,69,74,75,[77][78][79][80]84,87,88,[91][92][93][94][95][96]98,100,106,107].…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

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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Section: Introductionmentioning

confidence: 89%

Section: Comparisons With Other Methodsmentioning

confidence: 99%

Section: The Second-order Filtermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

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

2020

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“…Most tunings methods for first-order integrating systems with time-delay can also be applied in higher-order systems by approximating the process as an IFOTD model [30,[32][33][34][35]39,40,[43][44][45]47,48,50,51]. Controller design based on IMC PID tuning rules was proposed by Kumar and Padma Sree [18], Skogestad [39], Jin and Liu [43], Panda [41], Ghousiya Begum et al [35], and Najafizadegan et al [34].…”

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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Modified Smith predictor‐based all‐proportional‐derivative control for second‐order delay‐dominated integrating processes

Karan

Dey

2020

Asia-Pacific J Chem Eng

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An all-proportional-derivative (PD) control-based modified Smith predictor design is reported here for second-order delay-dominated integrating processes. The proposed control structure is realized with two PD controllers along with a first-order filter towards achieving the desired closed-loop response. To eliminate the tuning complexity, reported internal model control (IMC) scheme suggests a single tuning parameter λ (i.e. closed-loop time constant) to tune both the PD controllers along with the filter present in the modified Smith predictor designing. The forward path PD controller parameters are obtained as per the IMC tuning guideline suggested for servo tracking, whereas the feedback path PD controller is realized based on Routh stability analysis with a goal towards improved regulatory responses. The firstorder filter present in the feedback path helps to ensure robust closed-loop performance. Considerable performance enhancement is observed during set point tracking by the proposed scheme where no overshoot is observed even with smaller rise time. In addition, smooth and reasonably quick load rejection behaviour is also found during a regulatory response. Superiority of the proposed scheme is also substantiated in comparison with others' reported dead-time compensating techniques in terms of closed-loop performance indices as well as stability margins.

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Novel proportional–integral–derivative controller with second order filter for integrating processes

Cited by 26 publications

References 21 publications

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

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

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

Modified Smith predictor‐based all‐proportional‐derivative control for second‐order delay‐dominated integrating processes

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