Design of a novel fractional‐order internal model controller‐based Smith predictor for integrating processes with large dead‐time

Kumar, Deepak; Aryan, Pulakraj; Raja, G. Lloyds

doi:10.1002/apj.2724

Cited by 31 publications

(15 citation statements)

References 40 publications

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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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Section: Methodsmentioning

confidence: 99%

Auto-Tuning PID Controller Based on Genetic Algorithm

Figueiredo¹,

Toso²,

Schmith³

2023

Disturbance Rejection Control

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“…Authors [38] had chosen a classical PID with setpoint weighting concept. In Das et al authors, [12] developed 2 DOF PID, while in Kumar et al [10], a multiloop configuration with Smith predictor structure with FoIMC was proposed.…”

Section: Example-1mentioning

confidence: 99%

“…These works obtained results with high-order classical controllers with additional filters or fractional orders. For a numerical study, recent works provided by Das et al [12], Sengupta et al [22], Kumar et al [10], Karan and Dey [37], Wang et al [38], and Papadopoulos et al [39] were taken into consideration. The indicators such as the controller energy (TV), settling time (t s in second), and ITSE index were calculated for setpoint and load disturbance.…”

Section: Numerical Studymentioning

confidence: 99%

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Direct synthesis approach to design PDμ${\text{PD}}^\mu$ based smith predictor for integrating plants: Studied on a quadrotor UAV

Ranjan,

Mehta,

Prakash

et al. 2024

The Journal of Engineering

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This article presents a simple yet novel method of designing a fractional‐order proportional derivative (namely, ) controller for all types of integrating plants. Considering the importance of the direct synthesis approach, the method obtains robust closed‐loop performance. The setpoint parameter is obtained using the multi‐optimization Pareto solution, considering the optimal values in control efforts and performance index together. The numerical investigations have shown improved servo and regulatory responses compared to recently published strategies with fractional orders. It is also known that classical PIDs cannot accurately follow a ramp setpoint. A real‐world situation also demands that the reference inputs become an acceleration ramp type. The proposed technique can handle rising ramp setpoints with plant uncertainty and measurement noise. Hardware verification is also performed on a quadrotor minidrone to check for real‐time issues.

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“…Moreover, there are relatively less studies pertaining to multi-loop control structures when compared to PID controller design for unity feedback structures. Furthermore, the closed-loop behavior of the prevailing multi-loop control strategies can be enhanced by using fractional-order controllers [47][48][49][50][51]. Badri and Soojodi [52] have recommended a stabilization theorem on fractional-order linear time-invariant systems with different fractional-orders.…”

Section: Introductionmentioning

confidence: 99%

Improved fractional augmented control strategies for continuously stirred tank reactors

Mukherjee

Raja

Kundu

et al. 2022

Asian Journal of Control

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Controlling concentration and temperature of continuously stirred tank reactor (CSTR) is an extremely challenging task in chemical process industries. This is because conventional unity feedback schemes do not guarantee stable operating conditions for the CSTR process. Therefore, fractional calculus is augmented with multi‐loop control to achieve enhanced stability and closed‐loop performance than unity feedback structure in this work. Accordingly, three different fractional‐order‐based novel multi‐loop control structures are proposed based on time domain analysis. In two of the proposed strategies, fractional‐order PID controller (FOPID) and internal model control (IMC)‐based FOPID controller with fractional filter are used in the inner‐loop. Moreover, fractional‐order‐based Lyapunov stability rule of model reference adaptive control (MRAC) is used in outer‐loops for both of the above mentioned methods. Finally, an advanced multi‐loop predictor with FOPD controller in the inner‐loop and FOIMC controller in the outer‐loop is also proposed. In this work, fractional‐order, filter parameters, and FOPID settings are obtained by minimizing multi‐objective functions using modified particle swarm optimization (PSO) algorithm. Closed‐loop responses and control efforts of the proposed control strategies are compared with that of FO‐Lyapunov‐based MRAC scheme. Quantitative performance analysis is also carried out on all proposed methods based on error metrics and total variation of the control signal.

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Design of a novel fractional‐order internal model controller‐based Smith predictor for integrating processes with large dead‐time

Cited by 31 publications

References 40 publications

Auto-Tuning PID Controller Based on Genetic Algorithm

Auto-Tuning PID Controller Based on Genetic Algorithm

Direct synthesis approach to design PDμ${\text{PD}}^\mu$ based smith predictor for integrating plants: Studied on a quadrotor UAV

Improved fractional augmented control strategies for continuously stirred tank reactors

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