scholarly journals Kontrol Fuzzy PI untuk Pengaturan Kecepatan Angin oleh Wind Generator 1.42 Hp pada Wind Tunnel

2020 ◽  
Vol 8 (2) ◽  
pp. 288
Author(s):  
SEPTYANA RISKITASARI ◽  
BUDHY SETIAWAN ◽  
RATNA IKA PUTRI ◽  
WAHYU AULIA NURWICAKSANA
Keyword(s):  
Wind Tunnel ◽  
Fuzzy Control ◽  
Induction Motor ◽  
Control Method ◽  
Control Design ◽  
Pi Control ◽  
Response System ◽  
Wind Generator ◽  
Turn Around Time ◽  
The Stability

ABSTRAKWind generator merupakan bagian terpenting dari pembuatan Wind tunnel, dimana fungsinya adalah sebagai sumber penghasil angin. Pada proses desain kontrol, tahap pertama adalah mengumpulkan data parameter empiris wind generator real menggunakan jenis motor induksi 1.42 hp pada wind tunnel. Pada penelitian ini dibuat simulasi pengontrolan kecepatan generator angin menggunakan metode kontrol fuzzy PI untuk meningkatkan hasil dari respon sistem kestabilan dengan titik setel 2 m/s hingga 10 m/s. Simulasi kontrol dilakukan dengan memanfaatkan jenis motor induksi yang sebanding dengan plant. Hasil respon sistem dengan menggunakan metode kontrol PI dan kontrol fuzzy PI yaitu kontrol fuzzy PI menghasilkan respon sistem yang lebih stabil dibandingkan dengan kontrol PI yang menghasilkan respons berosilasi. Settling time tercepat dengan kontrol fuzzy PI yaitu pada kecepatan angin 4 m/s sebesar 0.05 detik.Kata Kunci: Motor Induksi, Wind Generator, Wind Tunnel, Fuzzy PI ABSTRACTThe wind generator is the most important part of making a wind tunnel as a source of wind. In the control design process, the first step is to collect the real wind generator data parameters, namely the 1.42 hp induction motor in the wind tunnel. In this study, a simulation using a type of induction motor that is comparable to a plant with the fuzzy PI control method to improve the results of the stability of the response system with a set point of 2 m/s to 10 m/s. The results of the response system using the PI control and the PI Fuzzy control that is the PI Fuzzy control produce a more stable response system compared to the PI control which produces an oscillating response. The fastest turn around time with the PI Fuzzy control at a wind speed of 4 m/s is 0.05 seconds.Keywords: Induction Motor, Wind Generator, Wind Tunnel, PI Fuzzy

A Novel Fuzzy Self-Adaption PI Control Method of the Var Compensation of Wind Generator

2012 ◽  
Vol 608-609 ◽  
pp. 785-789 ◽  
Author(s):  
Xian Ming Zou ◽  
Jun Yang ◽  
Hongyu Zhang ◽  
Yu Zhu
Keyword(s):  
Reactive Power ◽  
Control Method ◽  
Wind Farms ◽  
Normal Operation ◽  
Pi Control ◽  
Doubly Fed Induction Generator ◽  
Wind Generator ◽  
Novel Method ◽  
Doubly Fed ◽  
The Stability

Aiming at the phenomenon that the doubly fed induction generator (DFIG) can supply active power and absorb reactive power in the range of normal operation involves stability and transient, this paper proposes a novel method based on the fuzzy self-adaption PI control to control TCR to compensate the reactive power of wind farms required, and to improve the stability of voltage in wind farms. In this research, the wind generator model of being regarded as reactive load is established in Simulink of MATLAB. The results show that: the voltage and current distortion of the wind generator can be restrained well by using the SVC system proposed in this paper, and the stability of voltage and current in wind farms can be improved effectively.

Predictive torque control of induction motor based on improved fuzzy control method

2013 ◽  
Author(s):  
Mohammad Javad Lesani ◽  
Hamid Mahmoudi ◽  
Masoud Ebrahim ◽  
Seighalani Varzali ◽  
Davood Arab khaburi
Keyword(s):  
Fuzzy Control ◽  
Induction Motor ◽  
Control Method ◽  
Torque Control

Switching Control Design for Switched Fuzzy Discrete-Time Systems

2014 ◽  
Vol 1006-1007 ◽  
pp. 711-714
Author(s):  
Hong Yang ◽  
Huan Huan Lü ◽  
Le Zhang
Keyword(s):  
Stability Analysis ◽  
Discrete Time ◽  
Fuzzy Systems ◽  
Closed Loop ◽  
Control Method ◽  
Control Design ◽  
Switching Control ◽  
Discrete Time Systems ◽  
The Stability ◽  
Time Systems

This paper investigates the problems of stability analysis and stabilization for a class of switched fuzzy discrete-time systems. Based on a common Lyapunov functional, a switching control method has been developed for the stability analysis of switched discrete-time fuzzy systems. A new stabilization approach based on a switching parallel distributed compensation scheme is given for the closed-loop switched fuzzy systems. Finally, the illustrative example is provided to demonstrate the effectiveness of the techniques proposed in this paper.

scholarly journals Pemodelan Direct Quadrate (D-Q) Pada Kendali Kecepatan Motor Induksi Tiga Phasa dengan Field Oriented Control (FOC) Berbasis Kendali P-I

2019 ◽  
Vol 1 (2) ◽  
pp. 25
Author(s):  
Rizana Fauzi ◽  
Jumaddil Khair
Keyword(s):  
Induction Motor ◽  
Induction Motors ◽  
Reference Value ◽  
Operating Conditions ◽  
System Response ◽  
Pi Control ◽  
Field Oriented Control ◽  
Proportional Integral ◽  
Speed Regulation ◽  
The Stability

The utilization of a 3 phase induction motor is increasingly developing, so research on speed regulation in 3 phase induction motors is also increasingly widely studied. This is because the use of 3 phase induction motors in the industry and especially hybrid vehicles are increasingly being developed. But there are some disadvantages of induction motors, one of which is the characteristics of non-linear parameters, especially rotor resistance which has varying values for different operating conditions, so it cannot maintain its speed constantly if there is a change in load. This, of course, can affect the performance of an induction motor. To get a constant speed and better system performance on load changes a controller is needed. This study aims to model direct-quadrate parameters (D-Q) using the Field Oriented Control (FOC) method based on the Proportional-Integral (PI) controller. With the d-q parameter controlled, the induction motor will be more stable, because the d-q parameter determines the stability of the change in torque and flux in the induction motor. Proportional-Integral (PI) control used is a classic control system that is easy because it does not need to look for a mathematical model of the system, but it remains effective because it has a fairly stable system response, by setting the best combination of proportional (Kp) constants and Integrator constants ( Ki). In the results of the implementation, it can be seen that the use of FOC can be used as an approach in terms of setting the speed of the induction motor, and with the use of the PI control can help the output response get better with a shorter response time to reach the reference value.

scholarly journals A probabilistic robust mixed H2/H∞ fuzzy control method for hypersonic vehicles based on reliability theory

2018 ◽  
Vol 15 (1) ◽  
pp. 172988141775415 ◽  
Author(s):  
Xiaomeng Yin ◽  
Xinming Li ◽  
Lei Liu ◽  
Yongji Wang ◽  
Xing Wei
Keyword(s):  
Fuzzy Control ◽  
Flight Control ◽  
Control Method ◽  
Fuzzy Controller ◽  
Fuzzy Model ◽  
Control Design ◽  
Hypersonic Vehicle ◽  
Linear Matrix ◽  
Hypersonic Vehicles ◽  
Robust Fuzzy Controller

Achieving balance between robustness and performance is always a challenge in the hypersonic vehicle flight control design. In this research, we focus on dealing with uncertainties of the fuzzy control system from the viewpoint of reliability. A probabilistic robust mixed H2/ H∞ fuzzy control method for hypersonic vehicles is presented by describing the uncertain parameters as random variables. First, a Takagi–Sugeno fuzzy model is employed for the hypersonic vehicle nonlinear dynamics characteristics. Next, a robust fuzzy controller is developed by solving a reliability-based multi-objective linear matrix inequality optimization problem, in which the H2/ H∞ performance is optimized under the condition that the system is robustly reliable to uncertainties. By this method, the system performance and reliability can be taken into account simultaneously, which reduces the conservatism in the robust fuzzy control design. Finally, simulation results of a hypersonic vehicle demonstrate the feasibility and effectiveness of the presented method.

OBSERVER-BASED FUZZY CONTROL DESIGN FOR DISCRETE-TIME T-S FUZZY BILINEAR SYSTEMS

2013 ◽  
Vol 21 (03) ◽  
pp. 435-454 ◽  
Author(s):  
JIANGRONG LI ◽  
JUNMIN LI ◽  
ZHILE XIA
Keyword(s):  
Fuzzy Control ◽  
Discrete Time ◽  
Control Design ◽  
Bilinear System ◽  
Single Step ◽  
Bilinear Systems ◽  
Linear Matrix ◽  
Fuzzy Observer ◽  
Nonlinear Minimization ◽  
The Stability

This paper is concerned with the problem of observer-based fuzzy control design for discrete-time T-S fuzzy bilinear systems. Based on the piecewise quadratic Lyapunov function (PQLF), the piecewise fuzzy observer-based controllers are designed for T-S fuzzy bilinear systems. It is shown that the stability for discrete T-S fuzzy bilinear system can be established if there exists a PQLF can be constructed and the fuzzy observer-based controller can be obtained by solving a set of nonlinear minimization problem involving linear matrix inequalities(LMIs) constraints. An iterative algorithm making use of sequential linear programming matrix method (SLPMM) to derive a single-step LMI condition for fuzzy observer-based control design. Finally, an illustrative example is provided to demonstrate the effectiveness of the results proposed in this paper.

scholarly journals PERFORMANCE ANALYSIS FUZZY-PID VERSUS FUZZY FOR QUADCOPTER ALTITUDE LOCK SYSTEM

2015 ◽  
Vol 77 (22) ◽  
Author(s):  
Hendi Wicaksono ◽  
Yohanes Gunawan ◽  
Arbil Yodinata ◽  
Leonardie Leonardie
Keyword(s):  
Performance Analysis ◽  
Fuzzy Control ◽  
Control Method ◽  
Fuzzy Controller ◽  
Sensor Data ◽  
Fuzzy Pid ◽  
Motor Speed ◽  
Fuzzy Pid Control ◽  
Comparative Performance ◽  
The Stability

Mostly quadcopter has a flight controller to receive signal from remote control to control four brushless motor speed. In this paper, the researchers introduced a new control method to make quadcopter altitude lock system using Fuzzy-PID and perform a comparative  performance analysis between the Fuzzy controller and the new Fuzzy-PID controller. Fuzzy controller has ability to solve uncertainty within the system, by incorporating with altitude sensor data. On the other hand, Fuzzy-PID has the ability to gain the target level with Kp, Ki, Kd values controlled. In this paper the researchers present an analysis to compare the control method between Fuzzy and Fuzzy-PID with regards to the stability altitude lock system. The stability of the altitude lock system can be measured by how small the oscillations occurred. Fuzzy control has shown to produce better result than Fuzzy-PID control. Fuzzy control has 14 cm as its average oscillation, while Fuzzy-PID recorded 24 cm as its average oscillation.  

Nonlinear optimal control for ship propulsion systems comprising an induction motor and a drivetrain

2019 ◽  
Vol 234 (2) ◽  
pp. 409-425
Author(s):  
Gerasimos Rigatos ◽  
Pierluigi Siano ◽  
Masoud Abbaszadeh
Keyword(s):  
Induction Motor ◽  
Control Method ◽  
Taylor Series Expansion ◽  
Algebraic Riccati Equation ◽  
Time Step ◽  
Propulsion Systems ◽  
H Infinity ◽  
Approximate Linearization ◽  
The Stability ◽  
Linearized Model

The article proposes a nonlinear optimal [Formula: see text] control method for electric ships’ propulsion systems comprising an induction motor, a drivetrain and a propeller. The control method relies on approximate linearization of the propulsion system’s dynamic model using Taylor series expansion and on the computation of the state-space description’s Jacobian matrices. The linearization takes place around a temporary operating point which is recomputed at each time-step of the control method. For the approximately linearized model of the ship’s propulsion system, an H-infinity (optimal) feedback controller is developed. For the computation of the controller’s gains, an algebraic Riccati equation is solved at each iteration of the control algorithm. The stability properties of the control method are proven through Lyapunov analysis.

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