A New Reduced-Order Implementation of Discrete-Time Fractional-Order PID Controller

Stanisławski, Rafał; Rydel, Marek; Li, Zhixiong

doi:10.1109/access.2022.3150883

Cited by 20 publications

(6 citation statements)

References 54 publications

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“…where ∇ −λ (q) and ∇ µ (q) are the backward (nabla) discrete-time fractional-order integrator and difference, q is the forward shift operator, and h is the sample time [43]. The nabla fractional-order difference can be defined by the use of the discrete-time Grünwald-Letnikov operator as…”

Section: Discrete Fractional Pid Controllermentioning

confidence: 99%

Experimental Validation of Fractional PID Controllers Applied to a Two-Tank System

et al. 2023

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An experimental validation of fractional-order PID (FOPID) controllers, which were applied to a two coupled tanks system, is presented in this article. Two FOPID controllers, a continuous FOPID (cFOPID) and a discrete FOPID (dFOPID), were implemented in real-time. The gains tuning process was accomplished by applying genetic algorithms while considering the cost function with respect to the tracking error and control effort. The gains optimization process was performed directly to the two-tanks non-linear model. The real-time implementation used a National Instruments PCIe-6321 card as a data acquisition system; for the interface, we used a Simulink Matlab and Simulink Desktop Real-Time Toolbox. The performance of the fractional controllers was compared with the performance of classical PID controllers.

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Section: Discrete Fractional Pid Controllermentioning

confidence: 99%

Experimental Validation of Fractional PID Controllers Applied to a Two-Tank System

et al. 2023

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“…Another reduced-order representation of FO-PIDs starting from ORA approximation is designed in [16]. In terms of numerical implementation, a discrete-time and low-order approximation method for FO-PID controllers is presented in [17]. However, if the above mentioned order reduction steps are applied, the resulting controller does not necessary fulfill the robust stability and the robust performance criteria.…”

Section: A Literature Reviewmentioning

confidence: 99%

Reduced-Order Approximation of Fractional-Order Controllers by keeping Robust Stability and Robust Performance

Mihaly

Şuşcă

Birs

et al. 2023

2023 American Control Conference (ACC)

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Recently, the fractional-order element has been integrated into the Robust Control Framework considering the Oustaloup method. As such, the resulting infinite impulse response approximation manages to satisfy the robust stability and the robust performance criteria according to a given uncertainty block. However, the recommended approximation order for each fractional-order element is the number of decades of the frequency range where the approximation is valid, which can lead to a high-order controller. The current paper describes an optimization-based technique to find a loworder approximation of a fractional-order controller such that the resulting controller maintains the robust stability and robust performance as well. A set of numerical experiments have also been performed in order to illustrate the proposed method.

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“…Designing an effective controller is challenging due to the interactions between the loops. For the conventional single-input, single-output (SISO) proportional-integralderivative (PID) controller, a number of tuning techniques are offered [6]. The design approaches that should be taken into account when designing fractional controllers are also outlined.…”

Section: Introductionmentioning

confidence: 99%

Improved Decentralized Fractional-Order Control of Higher-Order Systems Using Modified Flower Pollination Optimization

Hamza

2024

Algorithms

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Due to increased complexity and interactions between various subsystems, higher-order MIMO systems present difficulties in terms of stability and control performance. This study effort provides a novel, all-encompassing method for creating a decentralized fractional-order control technique for higher-order systems. Given the greater number of variables that needed to be optimized for fractional order control in higher-order, multi-input, multi-output systems, the modified flower pollination optimization algorithm (MFPOA) optimization technique was chosen due to its rapid convergence speed and minimal computational effort. The goal of the design is to improve control performance. Maximum overshoot (Mp), rising time (tr), and settling time (ts) are the performance factors taken into consideration. The MFPOA approach is used to improve the settings of the proposed decentralized fractional-order proportional-integral-derivative (FOPID) controller. By exploring the parameter space and converging on the best controller settings, the MFPOA examines the parameter space and satisfies the imposed constraints by maintaining system stability. To evaluate the suggested approach, simulation studies on two systems are carried out. The results show that by decreasing the loop interactions between subsystems with improved stability, the decentralized control with the MFPOA-based FOPID controller provides better control performance.

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A New Reduced-Order Implementation of Discrete-Time Fractional-Order PID Controller

Cited by 20 publications

References 54 publications

Experimental Validation of Fractional PID Controllers Applied to a Two-Tank System

Experimental Validation of Fractional PID Controllers Applied to a Two-Tank System

Reduced-Order Approximation of Fractional-Order Controllers by keeping Robust Stability and Robust Performance

Improved Decentralized Fractional-Order Control of Higher-Order Systems Using Modified Flower Pollination Optimization

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