Hovering Control of Quadrotor Based on Fuzzy Logic

2017 ◽  
Vol 8 (1) ◽  
pp. 492
Author(s):  
Nia Maharani Raharja ◽  
Eka Firmansyah ◽  
Adha Imam Cahyadi ◽  
Iswanto Iswanto
Keyword(s):  
Fuzzy Logic ◽  
Rise Time ◽  
Control Algorithm ◽  
Fuzzy Logic Controller ◽  
Settling Time ◽  
Altitude Control ◽  
Rotary Wing ◽  
Hovering Control ◽  
Maximum Rise

Quadrotor is one of rotary wing UAV types which is able to perform a hover position. In order to take off, landing, and hover, it needs controllers. Conventional controllers have been widely applied in quadrotor, yet they have drawbacks namely overshoot. This paper presents attitude and altitude control algorithm in order to obtain a response as quadrotor hovered optimally within minimum overshoot, rise time, and settling time. The algorithm used is Fuzzy Logic Controller (FLC) algorithm with Mamdani method. By using the algorithm, the quadrotor is able to hover with minimum overshoot and maximum rise time. The advantage of the algorithm is that it does not require linearization model of the quadrotor.

STABILISASI TEGANGAN KELUARAN BUCK CONVERTER DENGAN METODE FUZZY LOGIC CONTROLLER

JURNAL ELTEK ◽  
2018 ◽  
Vol 16 (2) ◽  
pp. 125
Author(s):  
Oktriza Melfazen
Keyword(s):  
Fuzzy Logic ◽  
Steady State ◽  
Rise Time ◽  
Fuzzy Logic Controller ◽  
Buck Converter ◽  
Settling Time

Buck converter idealnya mempunyai keluaran yang stabil, pemanfaatandaya rendah, mudah untuk diatur, antarmuka yang mudah dengan pirantiyang lain, ketahanan yang lebih tinggi terhadap perubahan kondisi alam.Beberapa teknik dikembangkan untuk memenuhi parameter buckconverter. Solusi paling logis untuk digunakan pada sistem ini adalahmetode kontrol digital.Penelitian ini menelaah uji performansi terhadap stabilitas tegangankeluaran buck converter yang dikontrol dengan Logika Fuzzy metodeMamdani. Rangkaian sistem terdiri dari sumber tegangan DC variable,sensor tegangan dan Buck Converter dengan beban resistif sebagaimasukan, mikrokontroler ATMega 8535 sebagai subsistem kontroldengan metode logika fuzzy dan LCD sebagai penampil keluaran.Dengan fungsi keanggotaan error, delta error dan keanggotaan keluaranmasing-masing sebanyak 5 bagian serta metode defuzzifikasi center ofgrafity (COG), didapat hasil rerata error 0,29% pada variable masukan18V–20V dan setpoint keluaran 15V, rise time (tr) = 0,14s ; settling time(ts) = 3,4s ; maximum over shoot (%OS) = 2,6 dan error steady state(ess) = 0,3.

scholarly journals COMPARATIVE STUDY OF MAMDANI AND 1 ST -ORDER TAKAGI SUGENO KANG TYPE FUZZY LOGIC CONTROLLERS FOR CONTROLLING THE RIGID GANTRY CRANE SYSTEM

2018 ◽  
Vol 40 (2) ◽  
pp. 57
Author(s):  
Edwar Yazid ◽  
Rifa Rahmayanti
Keyword(s):  
Fuzzy Logic ◽  
Comparative Study ◽  
Rise Time ◽  
Fuzzy Logic Controller ◽  
Settling Time ◽  
Gantry Crane ◽  
Peak Time ◽  
Fuzzy Logic Controllers ◽  
Simulation Results ◽  
Takagi Sugeno

Controlling the rigid gantry crane system is challenging due to it being an under-actuated system. This paper addresses the challenge by presenting the fuzzy logic controller (FLC) with Mamdani and the 1 st -order Takagi Sugeno Kang (TSK) types presenting it in this comparative study. Both controllers are proposed to control the position of the crane while suppressing the swing of the payload. Simulation results show that the Mamdani type outperforms the 1 st -order Takagi Sugeno Kang (TSK) type in terms of no overshoot, though the earlier controller (Mamdani) has a slower rise time, settling time and peak time than the latter controller (TSK).

scholarly journals A PID-Type Fuzzy Logic Controller-Based Approach for Motion Control Applications

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5323 ◽  
Author(s):  
José R. García-Martínez ◽  
Edson E. Cruz-Miguel ◽  
Roberto V. Carrillo-Serrano ◽  
Fortino Mendoza-Mondragón ◽  
Manuel Toledano-Ayala ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Motion Control ◽  
Rise Time ◽  
Fuzzy Logic Controller ◽  
Dc Motor ◽  
Industrial Applications ◽  
Settling Time ◽  
Self Tuning ◽  
S Curve ◽  
Tuning Strategy

Motion control is widely used in industrial applications since machinery, robots, conveyor bands use smooth movements in order to reach a desired position decreasing the steady error and energy consumption. In this paper, a new Proportional-Integral-Derivative (PID) -type fuzzy logic controller (FLC) tuning strategy that is based on direct fuzzy relations is proposed in order to compute the PID constants. The motion control algorithm is composed by PID-type FLC and S-curve velocity profile, which is developed in C/C++ programming language; therefore, a license is not required to reproduce the code among embedded systems. The self-tuning controller is carried out online, it depends on error and change in error to adapt according to the system variations. The experimental results were obtained in a linear platform integrated by a direct current (DC) motor connected to an encoder to measure the position. The shaft of the motor is connected to an endless screw; a cart is placed on the screw to control its position. The rise time, overshoot, and settling time values measured in the experimentation are 0.124 s, 8.985% and 0.248 s, respectively. These results presented in part 6 demonstrate the performance of the controller, since the rise time and settling time are improved according to the state of the art. Besides, these parameters are compared with different control architectures reported in the literature. This comparison is made after applying a step input signal to the DC motor.

Data-Tuned Fuzzy Logic Controller Applied to a Horizontal Axis Wind System

2020 ◽  
Author(s):  
Lorenzo Dambrosio
Keyword(s):  
Fuzzy Logic ◽  
Wind Turbine ◽  
Control Algorithm ◽  
Fuzzy Logic Controller ◽  
Tracking Error ◽  
Synchronous Generator ◽  
Horizontal Axis ◽  
Fuzzy Rules ◽  
Wind System ◽  
Horizontal Axis Wind Turbine

Abstract This paper deals with the control problem concerning the output voltage frequency and amplitude regulation of a wind system power plant not connected to the supply grid. The wind system configuration includes a horizontal-axis wind-turbine which drives a synchronous generator. An appropriate modeling approach has been adopted for both the wind-turbine and the synchronous generator. The proposed controller makes use of the fuzzy logic environment in order to take advantage of the wind plant system informations integrated into a limited number of equilibrium condition points (input variable - output variable pairs). The fuzzy logic controller described in the present paper merges the most appropriate fuzzy rules clusters, based on the steady state working conditions. Then, thanks to a Least Square Estimator algorithm, the proposed control algorithm evaluates, for each sample time, the linear relation between control law correction and control tracking error levels. In order to demonstrate robustness of the suggested fuzzy control algorithm, two sets of results have been provided: the first one consider a fuzzy base with equally spaced rules, whereas, in the second set results, the number of fuzzy rules is reduced by a 25%.

Response Based Comparative Analysis of Two Inverter Fed Six Phase PMSM Drive by Using PI and Fuzzy Logic Controller

2016 ◽  
Vol 6 (6) ◽  
pp. 2643 ◽  
Author(s):  
Anurag Singh Tomer ◽  
Saty Prakash Dubey
Keyword(s):  
Fuzzy Logic ◽  
Comparative Analysis ◽  
Fuzzy Logic Controller ◽  
Permanent Magnet Synchronous Motor ◽  
Sudden Change ◽  
Pi Controller ◽  
Settling Time ◽  
Steady State Current ◽  
Speed Level ◽  
Starting Torque

<p>This Paper gives a complete modeling and simulation of a two inverter fed six phase permanent magnet synchronous motor drive system, Then response based comparative analysis is done on starting torque ,settling time, Steady state current at various speed levels and torque levels by changing  proportional- integral (PI) controller to  Fuzzy logic controller. The PI controller has some disadvantages like, more settling time, sluggish response due to sudden change in load torque etc. So an intelligent controller, based on fuzzy logic is introduced which replaces the PI-controller and its drawbacks. The performance of both the controller has been investigated and studied by comparing the different plots obtained by setting various speed level both incremented and decremented speed  , at different load conditions like No-load, fix load and dynamic load through Matlab/Simulink environment. Finally it is concluded from the result that fuzzy logic based controller is robust, reliable gives quick response with high starting torque and more effective than the conventional PI controller. It is also observed that both the proposed model can also run above rated speed significantally.</p>

scholarly journals Analisis Stabilitas Sistem Tenaga Listrik Dengan Automatic Generation Control (AGC) Dua Area Menggunakan Fuzzy Logic Controller

2018 ◽  
Vol 17 (2) ◽  
pp. 263
Author(s):  
Made Dwi Noviantara ◽  
I Nengah Suweden ◽  
I Made Mataram
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Frequency Response ◽  
Fuzzy Logic Controller ◽  
Frequency Control ◽  
Stable State ◽  
Automatic Generation ◽  
Settling Time ◽  
Frequency Control System ◽  
Response Output

The power system must be able to server the load in a sustainable manner with good service quality, such as constant voltage and frequency, quickly stabilized when load changes occur. The control generator automatically changes the frequency to the highest value when the system changes every time. This is called AGC. To keep the frequency in a stable state required frequency control system. Currently developing a lot of control system with fuzzy logic method. The simulation is performed using 5 membership functions and gives a loading of 0.1 pu, using MATLAB-Simulink software. From the analysis result, the comparison of output of frequency response in overshoot condition with conventional method yielded , settling time of 20.5 second. While the fuzzy logic controller method produces frequency response output in the overshoot state that is , settling time is 12 seconds. Whit the fuzzy logic controller method produces better performance and faster than conventional methods.

An investigation of fuzzy logic control of flexible robots

Robotica ◽  
1993 ◽  
Vol 11 (4) ◽  
pp. 363-372 ◽  
Author(s):  
Yueh-Jaw Lin ◽  
Tian-Soon Lee
Keyword(s):  
Fuzzy Logic ◽  
Control Algorithm ◽  
Fuzzy Logic Controller ◽  
Robot Manipulator ◽  
Nonlinear Effects ◽  
Control Law ◽  
Flexible Robot ◽  
Control Rules ◽  
Logic Control ◽  
The Mathematical Model

SUMMARYIn this paper a control law, which consists of a fuzzy logic controller plus a nonlinear effects negotiator for a flexible robot manipulator, is presented. The nonlinear effects negotiator is used to enhence the control system's ability in dealing with the uncertainty of the mathematical model. The control algorithm is simple and easy to tune as opposed to conventional control law which requires time consuming gains selections. To obtain fuzzy control rules, an error response plane method is proposed.

scholarly journals Meningkatkan kinerja motor induksi menggunakan teknologi fuzzy logic controller berbasis artificial intelligence

2021 ◽  
Vol 2 (2) ◽  
pp. 40-47
Author(s):  
I Putu Sutawinaya ◽  
◽  
Anak Agung Ngurah Made Narottama ◽  
Keyword(s):  
Artificial Intelligence ◽  
Fuzzy Logic ◽  
Steady State ◽  
Fuzzy Logic Controller ◽  
Settling Time ◽  
Peak Time ◽  
State Error

Motor induksi adalah merupakan motor listrik arus bolak balik (AC) yang umum digunakan pada industri-industri karena memiliki beberapa keuntungan, diantaranya relatif murah, kokoh serta handal. Namun kelemahan motor induksi saat terjadi perubahan torsi beban secara mendadak, maka akan terjadi penurunan kinerja (performansi) motor. Hal tersebut akan berpengaruh terhadap kestabilan putaran motor, di mana overshoot maupun undershoot relatif tinggi serta risetime relatif lambat. Untuk mengantispasi hal tersebut dibutuhkan sistem kontrol kecepatan motor induksi yang tentunya dapat meningkatkan kinerja motor induksi tersebut. Dalam penelitian ini dilakukan pengujian terhadap sistem kontrol kecepatan motor induksi menggunakan teknologi Fuzzy Logic Controller (FLC) melalui simulasi perangkat lunak Matlab. Dilakukan pengujian terhadap perubahan kinerja motor induksi melalui pemberian torsi beban serta setpoint yang berubah-ubah. Adapun hasil simulasi menunjukan bahwa performansi motor induksi, seperti undershoot, overshoot dan steady state error relatif kecil serta peak time, risetime dan settling time relatif cepat. Sistem yang dirancang mampu menurunkan arus start rata-rata sekitar 72,7% dan torsi awal rata-rata sekitar 81,8% terhadap kondisi idealnya.

scholarly journals Voltage Regulation in BDC Based on Fuzzy Logic Controller using Solar Power Generation

2019 ◽  
Vol 9 (2) ◽  
pp. 3481-3485
Keyword(s):  
Power Generation ◽  
Fuzzy Logic ◽  
Power Flow ◽  
Fuzzy Logic Controller ◽  
Sliding Mode ◽  
Harmonic Distortion ◽  
Voltage Regulation ◽  
Settling Time ◽  
Voltage Gain ◽  
Operating Modes

The PhotoVoltaic (PV) based grid system coupled with Bidirectional DC-DC Converter (BDC) utilize Fuzzy Logic Controller (FLC) for increasing voltage gain and reduce the settling time of DC link voltage than conventional is presented. BDC satisfied the load requirements, and control the power flow from different sources such as PV, grid, and battery. However, problems in conventional system are high Total Harmonic Distortion (THD), DC link voltage gain and settling time of capacitor voltage. The generated power is used for improving the power quality at the output of the inverter using Sliding Mode Controller (SMC). The converter and inverter operate has bidirectional performance and utilize the hybrid power generation as mentioned. The battery can act as a load based on operating modes of BDC and power generation. It provides a comparative analysis of Proportional Integral (PI) and FLC method that is effectively performs harmonic reduction in BDC.

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