Hybrid fuzzy-PID like optimal control  to reduce energy consumption

Maghfiroh, Hari; Hermanu, Chico; Ibrahim, Muhammad Hamka; Anwar, Miftahul; Ramelan, Agus

doi:10.12928/telkomnika.v18i4.14535

Cited by 17 publications

(17 citation statements)

References 15 publications

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“…It is the combination between LQR (Linear Quadratic Regulator) and Kalman Filter [25]. LQG solves the weakness of LQR control which requires the number of sensors as the number of states and replaces them with an observer, Kalman Filter [1]. This is very useful since not all the states of the system can be measured.…”

Section: B Lqg Designmentioning

confidence: 99%

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Speed Control of Induction Motor using LQG

Maghfiroh

Iftadi

Sujono

2021

jrc

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The electric motor is one of the technological developments which can support the production process. Not only in the manufacturing, but also in the transportation sector. The AC motor is divided into the synchronous and asynchronous motor. One type of asynchronous motor which widely used is the induction motor. In this study, the application of the IFOC control method and the LQG speed control method will be used to control the speed of an induction motor. The PID algorithm is also used as a comparison. Tests were carried out using MATLAB software. The speed variation and load variation are tested to validate the controller performance. PID is superior in terms of settling time and IAE. On the other hand, LQG is better in energy consumption. In terms of IAE, LQG has a higher value compared to PID by up to 56.67%. On the other hand, LQG is superior in terms of energy, which is 8.38% more efficient.

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Section: B Lqg Designmentioning

confidence: 99%

“…Base on the supply current, there are two kinds of an electric motor which are AC and DC motor. Although the DC motor is simpler in control, it uses a mechanical commutator (brush) which causes high maintenance cost [1]. Therefore, an AC motor is chosen.…”

Section: Introductionmentioning

confidence: 99%

Speed Control of Induction Motor using LQG

Maghfiroh

Iftadi

Sujono

2021

jrc

Self Cite

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“…Parameter adaptation with fuzzy logic is one option to improve the PI controllers [22]. This can be achieved using model reference adaptive control (MRAC) [23], [24], sliding mode or self tuning PIDs [16], [25]- [30].…”

Section: Bulletin Of Electr Eng and Infmentioning

confidence: 99%

DSP improvement of a vector speed induction motor control with a RST and adaptive fuzzy controller

et al. 2021

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The aim of this work is to improve the dynamics and to overcome the limitation of conventional fixed parameters PI controller used in induction motor (IM) field-oriented control (FOC). This study presents and implements a RST and an adaptive fuzzy controller (AFC) to enhance variable speed control. Theoretical background of theses controllers is outlined and then experimental results are presented. Practical implementation has been realized on a board with a 1.1 KW IM supplied by 10 KHz space vector pulse width modulation current regulated inverter used as power amplifier consisted of 300V, 10A IGBT and Matlab/Simulink environment. Test benches have been established under different operating conditions in order to evaluate and compare the performances of the PI, IP, and polynomial RST and adaptive fuzzy controllers. Parameter variations for the rotor and the inertia moment variation were done in order to compare and verify the robustness of each controller. High dynamic performances and robustness against parameters variation were obtained with the use of both RST and AFC.

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“…The traditional PID controller has a functional ease that allows engineers to activate it in a simple and direct way. The PID controller is linear and works very well within the bounds of the working point [3][4][5][6]. When the motor operates at different speed and load conditions the PID parameters must be retuned to the current operating conditions.…”

Section: Introductionmentioning

confidence: 99%

Numerous speeds-loads controller for DC-shunt motor based on PID controller with on-line parameters tuning supported by genetic algorithm

Alawan

Al-Furaiji

2021

IJEECS

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<p><span>Direct-current (DC) motor is a commonly used motor; its speed is directly affected by applying mechanical load. This paper proposes the design of wide speed-load range controller for a direct-current (DC) shunt motor based on proportional–integral–derivative (PID controller) with genetic system for controller parameters adjusting. The genetic based PID controller is simulated by using Matlab software package and tested with different sudden load values and different working speeds. A present control loop contains the suggested PID controller also Pulse-Width-Modulation PWM generator and H-bridge inverter. With the genetic system enhancement to parameters of developed PID controller, the results demonstration that this controller has great impact to preserve the profiles of the motor speed and produced torque after applied sudden load, and its intensification the motor performance at different speed and load conditions.</span></p>

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Hybrid fuzzy-PID like optimal control to reduce energy consumption

Cited by 17 publications

References 15 publications

Speed Control of Induction Motor using LQG

Speed Control of Induction Motor using LQG

DSP improvement of a vector speed induction motor control with a RST and adaptive fuzzy controller

Numerous speeds-loads controller for DC-shunt motor based on PID controller with on-line parameters tuning supported by genetic algorithm

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