Design of Indirect Fractional Order IMC Controller for Fractional Order Processes

Trivedi, Rishika; Padhy, Prabin Kumar

doi:10.1109/tcsii.2020.3013404

Cited by 30 publications

(22 citation statements)

References 27 publications

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“…Numerous performance measures are calculated under load disturbance 1 and 2 and addressed in Tables 14 and 15. These studies lead to the conclusion that the controller designed based on the proposed approach is less sensitive to the disturbances and robust against uncertainty in gain over existing FO-PID, 1 Fr-IMC, 23 IMC-PID, 27 IF-IMC, 31 and FO-IMC under δ ¼ 0. Load disturbance 1 and Load disturbance 2 are applied to the TFO-PTD process, at 250 and 500 s, with an amplitude of À40% and þ40% to the nominal value.…”

Section: Selection Of Fo Imc Controller Parametermentioning

confidence: 85%

“…The transfer function of TFO-PDT is written as, 31 and the proposed method are designed at M s ¼ 1:254. To obtain the desired M s , FO-PID, 1 Fr-IMC, 23 IF-IMC, 31 and proposed method requires, ω gc ¼ 0:5333, ϕ m ¼ 82:9372 and M s ¼ À0:280 and ψ ¼ À0:04, and δ ¼ À0:2804 respectively. Frequency response of fractional order controller and approximation technique was depicted in Figure 10.…”

Section: Selection Of Fo Imc Controller Parametermentioning

confidence: 99%

“…The proposed method's performance indices under servo response indicate that the IAE and ISE are 0.206 and 0.088, respectively. Likewise, IAE and ISE indices by FO-PID 1 method are 1.729, 0.938, IAE and ISE values by Fr-IMC 23 TFO-PDT process by the proposed method is compared with FO-PID, 1 Fr-IMC, 23 IMC-PID, 27 IF-IMC, 31 and FO-IMC under δ ¼ 0 controllers for servo and regulatory response as shown in Figure 11.…”

Section: Selection Of Fo Imc Controller Parametermentioning

confidence: 99%

“…Performance comparison of TFO-PDT process using numerous approaches Performance evaluation of different approaches on TFO-PDT process under load disturbance 1 Performance evaluation of different approaches on TFO-PDT process under both load disturbances FO-PID,1 Fr-IMC,23 IF-IMC,31 and FO-IMC controllers are proposed by Das et al, Li et al, Trivedi and Padhy,…”

mentioning

confidence: 99%

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Robust design of fractional order IMC controller for fractional order processes with time delay

Gnaneshwar

Trivedi

Padhy

2022

Int J Numerical Modelling

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This article presents a novel approach to the robust design of fractional order IMC controller for the fractional‐order (FO) plus time delay processes. The proposed methodology provides the flexibility to adjust the controller performance based on the application requirement using a single parameter. Also, it does not require any external filter. Thus, it ensures a better response over existing methods. A mathematical analysis is provided to select the tuning parameter to obtain the optimal solution. The effectiveness of the proposed methodology is measured for different FO processes with time delay using time‐domain specifications, performance indices and frequency domain parameters. Load disturbance analysis under various disturbances and robust analysis under uncertainty in process gain in the presence of the disturbances is carried out to study the sensitivity and robustness of the controller. The performance parameters are estimated in both analyses and compared with the different approaches available in the literature.

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Section: Selection Of Fo Imc Controller Parametermentioning

confidence: 85%

Section: Selection Of Fo Imc Controller Parametermentioning

confidence: 99%

Section: Selection Of Fo Imc Controller Parametermentioning

confidence: 99%

mentioning

confidence: 99%

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Robust design of fractional order IMC controller for fractional order processes with time delay

Gnaneshwar

Trivedi

Padhy

2022

Int J Numerical Modelling

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“…Some of the recent FO modeling studies in the existing literature such as conical water tank system, 14 wind turbines, 15 DC-DC converters, 16 thermal systems, 17 3-D RC network studies, 18 electroencephalographic (EEG) recorder systems, 19 voltage source converter, 20 modeling of coils, 21,22 RL and RC circuits, 23 three-phase voltage source PWM rectifier, 24 and PMSM speed servo system 25 are carried out. However, the non-linearities like core loss resistance and mutual inductance present in the IM makes the FO modeling study is somewhat complicated.…”

Section: Introductionmentioning

confidence: 99%

Design and analysis of a speed controller for fractional‐order‐modeled voltage‐source‐inverter‐fed induction motor drive

Adigintla

Aware

2022

Circuit Theory & Apps

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Summary This paper presents the fractional‐order voltage‐source‐inverter‐controlled induction machine (FO‐VSI‐IM) model extraction and integration to improve the closed‐loop speed control performance of variable speed drives. In the operating range of variable speed drive, it is susceptible to load disturbance and speed tracking error. This paper provides the practical approach to obtain the fractional‐order model of VSI‐fed induction motor (IM) drive by using PWM signal injection technique. The injected PWM signals and speed encoder response signals are recorded using the dSPACE 1104 platform. This model is used in constructing the closed‐loop speed control of VSI‐IM with designed integer‐order PI speed controller. The comparative performance is evaluated for FO‐VSI‐IM and integer‐order voltage‐source‐inverter‐controlled induction machine (IO‐VSI‐IM) with feed‐forward gain variations and load disturbances. It is observed that the robust speed tracking capability with the controller designed using the FO‐VSI‐IM model over the controller with IO‐VSI‐IM model under load disturbances. The improvement in speed tracking with less control effort in the FO‐VSI‐IM model is advantageous in field‐oriented control (FOC) drives.

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A neural network‐based design method of the fractional order PID controller for a class of motion control systems

Zheng

Chen

Wang

et al. 2021

Asian Journal of Control

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A neural network‐based design method for the fractional order proportional‐integral‐derivative ( PIλnormalDμ) controller is developed in this paper. The tuning process is divided into two steps: the integral and derivative orders of the controller are estimated by the neural networks, which are established according to the design specifications and the features of the plant; the remaining controller parameters are calculated according to the flat‐phase specification. In this way, the optimal PIλnormalDμ controller can be obtained without the optimization process. The effectiveness of the proposed method is studied via the application to a motion control system. The control performance of the controller tuned by the proposed method is compared with those tuned by some existing methods. Simulation and experimental results show that the controller obtained using the proposed method can offer good tracking performance and disturbance rejection performance for the control system.

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Design of Indirect Fractional Order IMC Controller for Fractional Order Processes

Cited by 30 publications

References 27 publications

Robust design of fractional order IMC controller for fractional order processes with time delay

Robust design of fractional order IMC controller for fractional order processes with time delay

Design and analysis of a speed controller for fractional‐order‐modeled voltage‐source‐inverter‐fed induction motor drive

A neural network‐based design method of the fractional order PID controller for a class of motion control systems

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