Optimal Fractional Order IMC-Based Series Cascade Control Strategy with Dead-Time Compensator for Unstable Processes

Mukherjee, Deep; Raja, G. Lloyds; Kundu, Palash Kumar

doi:10.1007/s40313-020-00644-2

Cited by 28 publications

(6 citation statements)

References 26 publications

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“…Using fractional‐order controller(s) for plants with dead‐time has become a fascinating research topic in recent years. [ 35–37 ] However, the design of double‐loop control structures with fractional‐order controllers for DIPTD plant models having substantial dead‐time is yet to be explored. There is also more scope for improving the closed‐loop performance of the existing strategies (for instance: eliminating the steady‐state error in Karan and Dey [ 34 ] ) by proper design of controllers.…”

Section: Introductionmentioning

confidence: 99%

Decoupled double‐loop FOIMC‐PD control architecture for double integral with dead time processes

2022

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A novel double‐loop control configuration with two controllers is suggested for double integrating processes with dead‐time. The stabilizing range of the inner‐loop proportional‐derivative (PD) controller is obtained using the Routh stability criteria. From this range, the exact PD settings are obtained by following a graphical approach where the integration of absolute error (IAE) is plotted for different PD settings. The PD settings resulting in the minimum IAE are chosen. In addition to stabilizing the plant, the inner‐loop also rejects the disturbances. A fractional‐order internal model controller (FOIMC) is designed for satisfactory set‐point tracking response in the outer‐loop. The suggested strategy has four adjustable parameters (proportional and derivative time constants, outer closed‐loop adjustment parameter, and fractional‐order of the FOIMC low‐pass filter). Based on extensive simulations, the tuning ranges for the above‐mentioned adjustable parameters are specified. The simulation study is done with the help of benchmark double integrating plant models with large dead‐time. Quantitative performance measures are also computed for comparing the suggested and previously reported schemes. The suggested FOIMC‐PD control architecture yields enhanced control performance than some recently reported techniques.

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Section: Introductionmentioning

confidence: 99%

Decoupled double‐loop FOIMC‐PD control architecture for double integral with dead time processes

2022

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“…For the GA design, the maximum ripple tolerance in steady state condition assumed for Ts determination was 0.5%. This 0.5% ripple is, on purpose, a restricted value in relation to the values assumed in control plants for regulatory response [17][18][19]. Further, the damping factor ξ and the undamped natural frequency ω n are computed by Eqs.…”

Section: Methodsmentioning

confidence: 99%

Auto-Tuning PID Controller Based on Genetic Algorithm

Figueiredo¹,

Toso²,

Schmith³

2023

Disturbance Rejection Control

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The PID controller is widely used in industry and its tuning is always a concern for the plant stabilization. Several methods for auto-tuning the PID have been proposed over the years, however, the relay method is the most used even though this method may determine nonideal PID gains and cause some physical stress on the plant. Here is presented a proposal for an auto-tuning PID controller based on a genetic algorithm. Genetic algorithm is a well-known method that imitates the natural selection process in order to obtain approximate solutions to optimization problems. Here, the method is presented in underdamped plants with the hypothesis that any plant can be approximated to a second-order function. From the unit step response of the system, the maximum overshoot and peak time were used in the GA evolution to obtain optimal PID parameters. The system was tested with a set of parameters and compared to MATLAB PID tuner function. Using the rising time and the settling time of unit step response from the closed loop system as validation parameters, the GA presented better results than the MATLAB tuner for most cases.

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“…It is observed the performance was improved with dual-loop and fractional-order than before. 27 A compensator-based series-cascade control with FOIMC was proposed for unstable processes in Mukherjee et al 28 In Chandran et al 7 and Pashaei and Bagheri, 29 the secondary controller was designed from FOIMC. In general, it is noticed that the fractional-order filter in IMC can provide a more flexibility to modify the output performances.…”

Section: Introductionmentioning

confidence: 99%

Improved control of integrating cascade processes with time delays using fractional-order internal model controller with the Smith predictor

Ranjan

Mehta

2023

Proceedings of the Institution of Mechanical Engineers, Part I:

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This article proposes an enhanced control of integrating cascade processes. The importance of the scheme shows by controlling a double integrating process with time delay under significant parametric uncertainties and load disturbances. A novel design is proposed based on the Smith predictor principle and uses a fractional-order internal model controller in the outer loop. The required fractional-order tuning parameter follows the desired gain and phase margins. At the same time, another tuning parameter, such as the fractional filter’s time constant, is calculated from the desired performance constraint. Numerical analysis and comparison are performed to showcase the feature of the hybrid structure. The simulation results show that the fractional-order internal model controller–based scheme provides enhanced tracking and faster regulation capabilities and works well under nominal and parameter uncertainty conditions.

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Optimal Fractional Order IMC-Based Series Cascade Control Strategy with Dead-Time Compensator for Unstable Processes

Cited by 28 publications

References 26 publications

Decoupled double‐loop FOIMC‐PD control architecture for double integral with dead time processes

Decoupled double‐loop FOIMC‐PD control architecture for double integral with dead time processes

Auto-Tuning PID Controller Based on Genetic Algorithm

Improved control of integrating cascade processes with time delays using fractional-order internal model controller with the Smith predictor

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