RETRACTED ARTICLE: Modified flower pollination
         algorithm for optimizing FOPID controller and its application with the programmable
            n-level inverter using fuzzy logic

Rajeswari, C.; Santhi, M.

doi:10.1007/s00500-020-05305-9

Cited by 9 publications

(5 citation statements)

References 22 publications

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“…where L(x) is the Levy-based step size showing the amount of pollination, δ is a scaling factor to control the step size, and u i n represents the n-th pollen or solution u n at iteration i. u best is the best solution among all the solutions thus far. As a result, L(x) is as in Equation (26).…”

Section: Flower Pollination Algorithm (Fpa)mentioning

confidence: 99%

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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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Section: Flower Pollination Algorithm (Fpa)mentioning

confidence: 99%

“…This is regarded as a considerable rate to be consumed in order to get the required results. More details regarding the drawbacks associated with the classical FPA are discussed in [26,27]. This paper adopted the MFPOA presented in [28].…”

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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“…In the conventional FPA, the AOG mutation is applied to global pollination's produced pollen after the pollination process. As a result, Equation ( 21) is transformed into Equation ( 27) following the mutation process [40]:…”

Section: Modified Fpamentioning

confidence: 99%

Modified Flower Pollination Optimization Based Design of Interval Type-2 Fuzzy PID Controller for Rotary Inverted Pendulum System

Hamza

2023

Axioms

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The Type 2 Fuzzy Logic System (T2FLS) is an enhanced form of the classical Fuzzy Logic System (FLS). The T2FLS based control technics demonstrated a lot of improvements for the past few decades. This is based on the advantage of its membership function (MF). Many experimental studies indicated the superiority of Type 2 Fuzzy Logic Controller (T2FLC) over the ordinary Type 1 Fuzzy Logic Controller (T1FLC), particularly in the event of non-linearities and complex uncertainties. However, the organized design method of T2FLCs is still an interesting problem in the control engineering community. This is due to the difficulties in computing the parameters associated it. A novel application of the Modified Flower Pollination (MFP) optimization algorithm in the design of T2FL is presented. The optimized Cascade Interval Type 2 Fuzzy PID Controller (IT2FPIDC) structure is proposed in this study. The best values of the parameters of the antecedent MFs and the PID gains of IT2FPIDC are found using the MFP algorithm. The MFP optimization technique was used because of its lower computational effort and high convergence speed, in view of the higher number of variables to be optimized in cascaded IT2FPIDC. The MFP-based Type-1 Fuzzy Proportional Integral Derivative Controller (T1FPIDC) is compared with the proposed MFP-based cascade-optimized IT2FPIDC. The rotary inverted pendulum (RIP) which is a non-minimum phase, non-linear, and unstable system is employed as a benchmark for testing the proposed controller. Balance and trajectory-tracking controls of the RIP are considered. Furthermore, the disturbance rejection ability of the proposed controller is analysed. The presented control methos is evaluated on the RIP manufactured by Quanser over many simulations and real-world experiments. The performance characteristics considered are steady state error (Ess), settling time (ts), maximum overshoot (Mp) and rise time (tr). The improvement of the effectiveness and robustness proposed controller in the presence of load disturbance, noise effects and parameter variation is shown.

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“…An effective search strategy is vital for improving the tracking efficiency of a visual target, and the flower pollination algorithm (FPA) has good global and local optimization ability simultaneously [19][20][21][22]. Therefore, this study introduces a position update equation of the FPA as the main optimization method of visual target tracking.…”

Section: ) Search Strategymentioning

confidence: 99%

Robust Visual Tracking Based on a Modified Flower Pollination Algorithm

Xiao

Yang

2021

IEEE Access

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RETRACTED ARTICLE: Modified flower pollination algorithm for optimizing FOPID controller and its application with the programmable n-level inverter using fuzzy logic

Cited by 9 publications

References 22 publications

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

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

Modified Flower Pollination Optimization Based Design of Interval Type-2 Fuzzy PID Controller for Rotary Inverted Pendulum System

Robust Visual Tracking Based on a Modified Flower Pollination Algorithm

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