General type industrial temperature system control based on fuzzy fractional-order PID controller

Liu, Lu; Xue, Dingyü; Zhang, Shuo

doi:10.1007/s40747-021-00431-9

Cited by 20 publications

(13 citation statements)

References 32 publications

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“…Another notable gap identified in the existing literature pertains to the treatment of fractional-order parameters within FOPID (Fractional-order Proportional Integral Derivative) controllers. A majority of the algorithms proposed in the literature resort to approximating the fractional parameters by mapping them to an integer-transfer function that closely resembles the desired response [5], [6], [7], [8], [9], [10], [13], [14], [30], [31], [33], [36], [37], [38]. This approach overlooks the inherent characteristics and advantages offered by fractional-order dynamics, thereby limiting the true potential and efficacy of FOPID controllers.…”

Section: Study Gapsmentioning

confidence: 99%

An Optimal Nonlinear Type-2 Fuzzy FOPID Control Design Based on Integral Performance Criteria Using FSM

Mohammad,

Al-Mbaideen,

Al-Odienat

et al. 2023

IEEE Access

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A fractional-order fuzzy proportional integral derivative (PID) controller is a controller that combines the benefits of fractional calculus and fuzzy logic with the conventional PID controller. In this paper, a four-stage optimization algorithm is proposed for the design of a Type-2 Fuzzy fractional-order PID controller based on the Fourier Series Method (FSM). Three distinct control structures are introduced: Type-2 fuzzy fractional PD + fractional PI controller, Type-2 fuzzy fractional PID, and Type-2 fuzzy fractional PD + Type-2 fuzzy fractional PI controller. In addition to a modified multi-performance criterion cost function, four integral performance criteria are employed as cost functions for each stage. The suggested algorithm avoids the utilization of the approximation equivalent for the fractional-order system and instead employs FSM. Furthermore, the approach optimizes the nonlinearity within the upper membership function (UMF) and the uncertainty range through the lower membership function, as opposed to arbitrary selection. By considering variations in the membership functions, the outcomes exhibit a superior response compared to previous investigations. The results of the three control structures are compared with the traditional PID controller, and simulation results demonstrate the feasibility of this technique. The findings suggest that by optimizing different integral performance criteria using this design technique, controllers for both integer and fractional-order plants can yield favorable step responses. The proposed algorithm is validated by comparing its step response performance with that of previous research, followed by a discussion on sensitivity analysis and computational requirements.INDEX TERMS Fourier series method, fractional-order PID controller, type-2 fuzzy controller.

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Section: Study Gapsmentioning

confidence: 99%

An Optimal Nonlinear Type-2 Fuzzy FOPID Control Design Based on Integral Performance Criteria Using FSM

Mohammad,

Al-Mbaideen,

Al-Odienat

et al. 2023

IEEE Access

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“…In view of this aspect, a Mamdani type fuzzy logic concept is combined with the FOPID controller in this work. Tis type of control approach is recently proposed in many works [53][54][55]. Te fuzzy-FOPID (FFOPID) controller could be a bunch of fuzzy-based rules connected in collection with PID control activity.…”

Section: Fuzzy Fopid Controller Designmentioning

confidence: 99%

Fuzzy Fractional-Order PID Control for PMSG Based Wind Energy Conversion System with Sparse Matrix Converter Topology

Abdulrazaq

Vural

2022

International Transactions on Electrical Energy Systems

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Sparse matrix converter (SMC) is an indirect AC-to-AC power electronic converter that has a fictitious DC link between rectification and inversion stages in which neither a capacitor nor an inductor, as the storage element, is utilized. Due to this advantage, SMC is used in AC drives, marine thrust systems, aerospace industry, as well as in wind energy applications. On the other hand, permanent magnet synchronous generator (PMSG) is competitive in wind turbine applications due to their prominent features. In this work, a fuzzy fractional-order PID (FFOPID) controller is designed for a PMSG based wind energy conversion system (WECS) which employs a three-phase three-level SMC. The FFOPID controller is chosen to combine the salient features of the fractional-order calculus and fuzzy logic operations to enhance the dynamic response of classical PID controller with fixed gains. The simulation results taken under different case studies are analyzed in detail, which demonstrate the superiority of the designed FFOPID controller over classical PID control approach in tracking d- and q-axis current references of the SMC at the output. With the designed control approach, the smooth control of the real and reactive power injections into the grid from the WECS are ensured with acceptable transient response.

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“…In fact, this control approach is renowned for its simple structure. However, tuning its parameters is a challenge that requires carrying out some strategies such as classical tuning rules, adaptation laws, optimal techniques, and fuzzy systems [6][7][8][9][10][11].…”

Section: Background and Motivationmentioning

confidence: 99%

Optimal Fuzzy Proportional‐Integral‐Derivative Control for a Class of Fourth‐Order Nonlinear Systems using Imperialist Competitive Algorithms

et al. 2022

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The proportional integral derivative (PID) controller has gained wide acceptance and use as the most useful control approach in the industry. However, the PID controller lacks robustness to uncertainties and stability under disturbances. To address this problem, this paper proposes an optimal fuzzy-PID technique for a two-degree-of-freedom cart-pole system. Fuzzy rules can be combined with controllers such as PID to tune their coefficients and allow the controller to deliver substantially improved performance. To achieve this, the fuzzy logic method is applied in conjunction with the PID approach to provide essential control inputs and improve the control algorithm efficiency. The achieved control gains are then optimized via the imperialist competitive algorithm. Consequently, the objective function for the cart-pole system is regarded as the summation of the displacement error of the cart, the angular error of the pole, and the control force. This control concept has been tested via simulation and experimental validations. Obtained results are presented to confirm the accuracy and efficiency of the suggested method.

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General type industrial temperature system control based on fuzzy fractional-order PID controller

Cited by 20 publications

References 32 publications

An Optimal Nonlinear Type-2 Fuzzy FOPID Control Design Based on Integral Performance Criteria Using FSM

An Optimal Nonlinear Type-2 Fuzzy FOPID Control Design Based on Integral Performance Criteria Using FSM

Fuzzy Fractional-Order PID Control for PMSG Based Wind Energy Conversion System with Sparse Matrix Converter Topology

Optimal Fuzzy Proportional‐Integral‐Derivative Control for a Class of Fourth‐Order Nonlinear Systems using Imperialist Competitive Algorithms

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