Investigation of performance of fuzzy logic controllers optimized with the hybrid genetic-gravitational search algorithm for PMSM speed control

Ünsal, Sinan; Aliskan, Ibrahim

doi:10.1080/00051144.2022.2036936

Cited by 19 publications

(14 citation statements)

References 50 publications

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“…Note from Table 3 that the advantages of the proposed method are the fast and finite-time convergence to the reference trajectory and robustness to parametric uncertainties and external disturbances. The error signal is converged to zero and the ISV and IAE criteria [41] are smaller than the other methods. Moreover, unlike the CSMC approach, the proposed method is free of the chattering phenomenon.…”

Section: Simulation Resultsmentioning

confidence: 88%

Design of an LMI-Based Fuzzy Fast Terminal Sliding Mode Control Approach for Uncertain MIMO Systems

Mokhtare

Mobayen

et al. 2022

Mathematics

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This paper proposes a linear matrix inequality (LMI)-based fuzzy fast terminal sliding mode control (FFTSM) approach for a multi-input multi-output (MIMO) system. This design aims to achieve the finite-time convergence of system trajectories to their desired values, while at the same time eliminating the chattering problem. Finite-time stability is proven using the Lyapunov theory and the control parameters are obtained using the LMI approach. The fuzzy logic approach is considered to fine tune the controller parameters and reduce the tracking error and control signal amplitude. The performance of the proposed approach is assessed using a simulation study of a direct current (DC) motor. The obtained results confirm the effectiveness of the proposed control design. Simplicity of the design, robustness, finite-time convergence, and chattering-free dynamics are among the features of the proposed approach.

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Section: Simulation Resultsmentioning

confidence: 88%

Design of an LMI-Based Fuzzy Fast Terminal Sliding Mode Control Approach for Uncertain MIMO Systems

Mokhtare

Mobayen

et al. 2022

Mathematics

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“…Even if the ANFIS have better results in the settling times, but the overshoot is much more noticeable which destroys the other transitory performance criteria. From the Table 4, it clearly shows that proposed GEO-ANFIS achieved better transient performance than existing HGA-GSA [17] and ANFIS. Table 5 clearly illustrates that the recommended GEO-ANFIS outperforms the conventional controllers in terms of settling time, rising time and overshoot time.…”

Section: Simulation Results and Discussionmentioning

confidence: 93%

“…Table 4 shows the comparative analysis of transient responses with existing HGA-GSA [17] and ANFIS controller. Even if the ANFIS have better results in the settling times, but the overshoot is much more noticeable which destroys the other transitory performance criteria.…”

Section: Simulation Results and Discussionmentioning

confidence: 99%

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Direct Torque Control for Permanent Magnet Synchronous Motor Using Golden Eagle Optimized ANFIS

2022

IJIES

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Nowadays, the Permanent Magnet Synchronous Motors (PMSM) are gaining popularity among electric motors due to their high efficiency, high-speed operation, ruggedness, and small size. PMSM motors comprise a trapezoidal electromotive force which is also called synchronous motors. Direct Torque Control (DTC) has been extensively applied in speed regulation systems due to its better dynamic behaviour. The controller manages the amplitude of torque and stator flux directly using the direct axis current. To manage the motor speed, the torque error, flux error, and projected location of flux linkage are employed to adjust the switching sequence of inverter. One of the most common problems encountered in a PMSM motor is Torque ripple, which is recreated by power electronic commutation and a better controller reduces the ripples to increase the drive's performance. Here, DTC control of PMSM is controlled by Golden Eagle Optimization (GEO) optimized Adaptive Neuro-Fuzzy Inference System (ANFIS). Learning parameters of the ANFIS are optimized for various operating functions by GEO in terms of speed and torque. In this work, simulation results are carried out in MATLAB, it shows that GEO-ANFIS controller is used in conjunction with a PMSM motor to attain less torque ripple up to 0.44 Nm and maintain the speed with a distortion error of 2.12 % when compared with Space Vector Pulse Width Modulation based DTC (SVPWM-DTC) and Dual Cost Function Model Predictive Direct Speed Control (DCF-MPDSC).

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“…Recently, meta-heuristic algorithms gained significant interest and demonstrated promising results in the multidimensional parameter optimisation of all types of nonconvex or non-smooth optimisation problems [13], [14]. Genetic algorithm (GA) [15], particle swarm optimisation algorithm (PSO) [16], gravitational search algorithm [17], grey wolf optimisation algorithm (GWO) [18], whale optimisation algorithm (WOA) [19], multi-verse optimisation algorithm (MVO) [20], and multi-objective grey wolf optimisation algorithm (MOGWO) [21] are highly preferred to find the optimum design parameters of any nonconvex problems. A PSO-based approach is proposed to optimise the weighting matrices of the optimal full-state controller (LQR) [22], [23].…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Optimisation-based Robust H∞ Controller Design Approach for a Multi-Level DC-DC Voltage Regulator

Keskin

Aliskan

2023

ELEKTRON ELEKTROTECH

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In case an analytical approach to the selection of any weighting function is not possible, the selection process is usually a random and time-consuming process. In robust H∞ control theory, the selection of scalar, time, or frequency-dependent weighting functions is the main issue to shape the amplitude-frequency characteristic curve of the feedback controller. Therefore, we propose a robust H∞ control approach which utilises the multi-objective grey wolf optimisation algorithm (MOGWO) to obtain the optimal performance weighting functions in the presence of right half-plane zeros and limited bandwidth constraints. A trade-off design flowchart is proposed, providing Pareto optimal solutions to choose the optimal configuration of the robust feedback controller. The control method is structured by combining the robust H∞ optimal technique and the multi-objective algorithm. The effectiveness of the approach is compared with the non-convex single-objective heuristic solutions like the multi-verse optimisation algorithm (MVO), whale optimisation algorithm (WOA), and grey wolf optimisation algorithm (GWO). The focus of this design is to track and stabilise the output voltage of the DC-DC converter in the presence of external disturbances and parameter uncertainties. The optimised controllers are implemented using a digital signal processor (DSP) on a 200 W interleaved boost converter. The simulation results and experimental findings show that the proposed control method provides supreme disturbance rejection along with maintaining the stability of the system.

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Investigation of performance of fuzzy logic controllers optimized with the hybrid genetic-gravitational search algorithm for PMSM speed control

Cited by 19 publications

References 50 publications

Design of an LMI-Based Fuzzy Fast Terminal Sliding Mode Control Approach for Uncertain MIMO Systems

Design of an LMI-Based Fuzzy Fast Terminal Sliding Mode Control Approach for Uncertain MIMO Systems

Direct Torque Control for Permanent Magnet Synchronous Motor Using Golden Eagle Optimized ANFIS

Multi-Objective Optimisation-based Robust H∞ Controller Design Approach for a Multi-Level DC-DC Voltage Regulator

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