An Improved Fractional Filter Fractional IMC-PID Controller Design and Analysis for Enhanced Performance of Non-integer Order Plus Time Delay Processes

Ranganayakulu, R.; Ambati, Rao; Gara, Babu

doi:10.18280/ejee.210203

Cited by 9 publications

(7 citation statements)

References 19 publications

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“…Although the perception on this proposition has been previously dealt with, yet they are confined only to some specific type of plants [22,23], especially limited to plants within relative orders equal to one. Moreover, very few of the available literatures discussed above have resorted to experimental validations of the methods put forward, with the IO time-delay plants solely described by first order transfer functions or only by simulation results for non-integer order time delayed plants [24].…”

Section: Introductionmentioning

confidence: 99%

Fractional order internal model control of non‐minimum phase and time‐delayed plants

Mondal

Dey

2023

Asian Journal of Control

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Several applications on fractional order (FO) control have gained considerable significance in the recent years, which led to the evolution of novel tuning strategies of the generalized order FO controllers. Some of the methods in available literatures are based on constrained minimization optimization techniques or analytical method defined only for specific plants. They are valid only for some special model cases. On the contrary, in this technical note, a generalized non-integer order internal model control (IMC) framework is realized for any order non-minimum phase (NMP) plants with right half plane (RHP) zero as well as time delayed plants having any finite relative order. Its parameters are graphically interpreted satisfying the frequency domain design stipulations for single input and single output (SISO) higher order linear time invariant (LTI) plants. The performance of the same on a bioreactor fermentation process for its temperature control is found to have outperformed in contrast to its integer order (IO)-IMC. It is therefore inferred here that this new approach pledges to impart unique solution of the controller parameters, formulating a highly efficient tool outperforming the existing paradigms. Simulation and real time experimentation are presented to validate the method put forward providing satisfactory performance in reference tracking, disturbance rejection, and robustness to various plant parameter perturbations. K E Y W O R D S fractional order (FO) control, internal model control (IMC), non-minimum phase unstable plants, time delayed plants

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Section: Introductionmentioning

confidence: 99%

Fractional order internal model control of non‐minimum phase and time‐delayed plants

Mondal

Dey

2023

Asian Journal of Control

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“…FOIMC based on the fractional order filter with the analytical design is discussed in [8]. [9][10] discussed implementation of fractional order controller (FOC).…”

Section: Introductionmentioning

confidence: 99%

Design of the fractional order internal model controller using the swarm intelligence techniques for the coupled tank system

Vavilala¹,

Thirumavalavan²,

Radhakrishnan³

et al. 2021

Turk J Elec Eng & Comp Sci

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The coupled tank system (comprising two tanks) is used in the chemical industries, water treatment plants etc. Level control of the coupled tank system is a common problem in the process control industry. This work proposes a fractional order internal model controller (FOIMC) with a higher order fractional filter for the level control of the coupled tank system. A first order plus delay time (FOPDT) model of the system is used in the controller design. FOIMC has advantages like robustness to changes in the system gain and extended stability margins. The proposed higher order fractional filter makes the controller physically realisable, and quickly roll off the magnitude Bode plot, neglecting the high frequency noise. The PSO algorithm is a swarm intelligence based algorithm used for the optimisation problems. The parameters of the FOIMC are optimised with the particle swarm optimisation (PSO) algorithm, by minimising an objective function constructed using time domain specifications. The novel objective function includes weighted peak overshoot, settling time, and integral square error. A MATLAB based tool, fractional order modelling and control (FOMCON) is used to simulate the fractional order controller. Performance of the proposed FOIMC is compared with two state of the art. Robustness to change in the operating point (tank height) is verified. The proposed FOIMC and the state of the art controllers are implemented on the laboratory setup, and the experimental results are compared.

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“…Proportional-integral-derivative controller (PID) is one of the most widely used process control strategies in industries like metallurgy, chemical industry, electric power, and machinery, thanks to its low requirement for system model, simple operation, high reliability, and strong robustness [1][2][3][4][5]. Fractional calculus is way more complex than integral calculus, which can identify commonly used systems.…”

Section: Introductionmentioning

confidence: 99%

A Fractional Order Proportional-Integral-Derivative Controller for Series Continuous Stirred Tank Reactor System

Wang

Yang

et al. 2021

Teh. vjesn.

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For series continuous stirred tank reactor system (CSTR), it is a complex problem to finetune the fractional order proportional-integral-derivative controller (FOPID). To solve the problem, this paper presents a parameter tuning method based on intelligent optimization genetic algorithm (GA) and integral time absolute error (ITAE). Firstly, the series CSTR system was mathematically modelled by vectorized modules, and an FOPID control system was established. Meanwhile, the intelligent optimization GA was introduced under the ITAE rule, and the empirical PID control parameters were taken as the initial values for iteration, aiming to enhance the effect of the search for optimal solution. To verify its superiority, the FOPID controller optimized by GA was compared with intelligent optimization GA and empirical PID controller through simulation. The results show that the optimized FOPID system achieved much better control effect and stronger anti-interference performance than the contrastive methods.

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An Improved Fractional Filter Fractional IMC-PID Controller Design and Analysis for Enhanced Performance of Non-integer Order Plus Time Delay Processes

Cited by 9 publications

References 19 publications

Fractional order internal model control of non‐minimum phase and time‐delayed plants

Fractional order internal model control of non‐minimum phase and time‐delayed plants

Design of the fractional order internal model controller using the swarm intelligence techniques for the coupled tank system

A Fractional Order Proportional-Integral-Derivative Controller for Series Continuous Stirred Tank Reactor System

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