An adaptive PI controller schema based on fuzzy logic controller for speed control of permanent magnet synchronous motors

Çelik, Emre; Dalcalı, Adem; Öztürk, Nihat; Canbaz, Ridvan

doi:10.1109/powereng.2013.6635698

Cited by 13 publications

(8 citation statements)

References 11 publications

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“…It is able to cope with the representation and manipulation of inherently uncertain and vague information, and establishes reasonable relationship between input and output variables by deploying linguistic terms [28]. The approach is very effective particularly in control systems that have substantial uncertainties, conflicting circumstances and complicated structures with no precise mathematical models [29][30][31][32]. However, depending on the availability and proper application of expert knowledge, design of FLSs may be tiresome, time-consuming, and even impossible at worst.…”

Section: Generation Of Current Reference Waveforms Using Ga-optimized Flementioning

confidence: 99%

Commutation current ripple minimization of brushless DC motor drive based on programmed phase current references

Çelik

Öztürk

2021

Electr Eng

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Although direct phase current control of brushless DC motor prevents commutation current ripple at low speed, it occurs at high speed which has not received the deserved attention in the literature. Dealing with this current ripple is of practical significance because commutation becomes more influential for high speeds as its duration and the current ripple's amplitude increase with speed. This paper concerns with the successful application of a fuzzy logic estimator (FLE) as an expert control technique to minimize the so-called current ripple profitably. Phase current reference waveforms are programmed as a function of commanded current, angular position, and commutation angle which is adjusted online by the developed FLE as per the motor working condition. The presented approach renders the current references with changing but equal slopes during commutation to keep the other phase current constant at all times. A genetic algorithm is also deployed to optimize the FLE's rule table. Unlike the reported researches, this study does not require calculating commutation time, and use of torque observer and/or commutation detection circuits. The acceptability of our proposal is widely illustrated by simulated and experimental results using DSP TMS320F28335, which signifies that prolific performance toward commutation current ripple minimization is achieved.

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Section: Generation Of Current Reference Waveforms Using Ga-optimized Flementioning

confidence: 99%

Commutation current ripple minimization of brushless DC motor drive based on programmed phase current references

Çelik

Öztürk

2021

Electr Eng

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“…Due to various uncertainties and nonlinearity exist in the PID structure, which makes it difficult to determine the PID gain, thus reducing the control system's performance [11]. Therefore, scholars have proposed a large number of intelligent algorithms such as metaheuristic optimization algorithm, fuzzy logic, differential evolution algorithm and deep neural network to improve the robustness of the control system [4][5][6][7][8][12][13][14][15][16][17][18][19][20]. Moreover, fuzzy logic-based methods provide better results than neural network and sliding mode control algorithms most of the time due to their offline training and chattering phenomenon [16,[21][22][23].…”

Section: Introductionmentioning

confidence: 99%

An adaptive fuzzy PID controller for speed control of brushless direct current motor

Wang

et al. 2022

SN Appl. Sci.

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Aiming at the problems of the poor adaptive ability in the current control methods for brushless DC motor, an adaptive fuzzy proportional integral derivative controller (AFPID) is proposed to realize the better control performance of speed for brushless DC motor. AFPID includes a conventional PID controller (C-PID) and PI + PD architectures with a configurable fuzzy logic controller (C-PID-FLC). The FLC in C-PID-FLC consists of two fuzzy inference engines, one is used to self-tune the parameters for PI control, the other is for the scaling factor self-tuning of PI control parameters. The PD structure in C-PID-FLC is mainly to reduce oscillation, overcome overshoot and speed up system response while effectively eliminating static errors. When the system reaches a certain stable state of rotation, AFPID adjusts the C-PID controller ground on the speed error, which saves control costs under the premise of ensuring control performance. AFPID adaptively realizes the respective advantages of C-PID and C-PID-FLC. Compared with other control methods, the merits of the proposed controller are highlighted. The results show that the AFPID controller has a better control performance regardless of changes in load disturbance and parameter variations. And through the change of mechanical parameters of brushless DC motor, the sensitivity of AFPID is analyzed.

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“…Fuzzy PI controller in general uses linear control theory applied by PI controller into Fuzzy control structure. This controller is capable to produce a performance similar to PI controller [15][16][17][18][19]. Modification can be done to the control surface of fuzzy in order to achieve better performance when dealt with non-linearity of the system [20].…”

Section: Introductionmentioning

confidence: 99%

Brushless DC Motor Speed Control Using Single Input Fuzzy PI Controller

Baharudin

Ayob

2018

IJPEDS

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<span lang="EN-US">Brushless DC (BLDC) motor is more reliable than classic DC motor with higher efficiency. Commonly used conventional linear controller such as PI, PID and PD controller. FLC is considered a replacement to conventional controller due to advantages on non-linear system. Hybrid controller e.g Fuzzy PI controller is developed to cope with drawback of both controller. Simplification of FLC in previous study is the pioneer of the idea of proposed method. Single-Input Fuzzy PI Controller (SIFPIC) is a hybrid controller that combines advantages of linear PI controller and fuzzy controller in one control structure. Since it is a single input based fuzzy controller, it yields simpler design and tuning process. Simulation is done using MATLAB/Simulink and the performance is observed through speed response under several conditions namely constant speed, changing seed and changing load torque. The performance of SIFPIC is compared with conventional PI and fuzzy PI controller. SIFPIC is as expected produced a response similar with the conventional fuzzy PI controller with both fuzzy based controller produce response with better dynamic.</span>

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An adaptive PI controller schema based on fuzzy logic controller for speed control of permanent magnet synchronous motors

Cited by 13 publications

References 11 publications

Commutation current ripple minimization of brushless DC motor drive based on programmed phase current references

Commutation current ripple minimization of brushless DC motor drive based on programmed phase current references

An adaptive fuzzy PID controller for speed control of brushless direct current motor

Brushless DC Motor Speed Control Using Single Input Fuzzy PI Controller

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