scholarly journals Control of Rotary Cranes Using Fuzzy Logic

2001 ◽  
Author(s):  
Amjed A. Al-mousa ◽  
Ali H. Nayfeh ◽  
Pushkin Kachroo
Keyword(s):  
Fuzzy Logic ◽  
Closed Loop ◽  
Fuzzy Logic Controller ◽  
Fuzzy Inference ◽  
Fuzzy Controller ◽  
Operating Conditions ◽  
Building Construction ◽  
Loop Control ◽  
Industrial Structures ◽  
Inference Engines

Abstract Rotary cranes (tower cranes) are common industrial structures that are used in building construction, factories, and harbors. These cranes are usually operated manually. With the size of these cranes becoming larger and the motion expected to be faster, the process of controlling them became difficult without using automatic control methods. In general, the movement of cranes has no prescribed path. Cranes have to be run under different operating conditions, which makes closed-loop control preferable. In this work a fuzzy logic controller is introduced with the idea of split-horizon; that is, fuzzy inference engines (FIE) are used for tracking the position and others are used for damping the load oscillations. The controller consists of two independent controllers: radial and rotational. Each of these controllers has two fuzzy inference engines (FTEs). Computer simulations are used to verify the performance of the controller. Three simulation cases are introduced: radial, compound, and damping. The results from the simulations show that the fuzzy controller is capable of keeping the load-oscillation angles small throughout the maneuvers while completing them in a relatively reasonable time.

scholarly journals Control of Rotary Cranes Using Fuzzy Logic

2003 ◽  
Vol 10 (2) ◽  
pp. 81-95 ◽  
Author(s):  
Amjed A. Al-mousa ◽  
Ali H. Nayfeh ◽  
Pushkin Kachroo
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Fuzzy Inference ◽  
Fuzzy Controller ◽  
Operating Conditions ◽  
Building Construction ◽  
Loop Control ◽  
Industrial Structures ◽  
Inference Engines ◽  
First Case

Rotary cranes (tower cranes) are common industrial structures that are used in building construction, factories, and harbors. These cranes are usually operated manually. With the size of these cranes becoming larger and the motion expected to be faster, the process of controlling them has become difficult without using automatic control methods. In general, the movement of cranes has no prescribed path. Cranes have to be run under different operating conditions, which makes closed-loop control attractive.In this work a fuzzy logic controller is introduced with the idea of “split-horizon”; that is, fuzzy inference engines (FIE) are used for tracking the position and others are used for damping the load oscillations. The controller consists of two independent sub-controllers: radial and rotational. Each of these controllers has two fuzzy inference engines (FIE). Computer simulations are used to verify the performance of the controller. Three simulation cases are presented. In the first case, the crane is operated in the gantry (radial) mode in which the trolley moves along the jib while the jib is fixed. In the second case (rotary mode), the trolley moves along the jib and the jib rotates. In the third case, the trolley and jib are fixed while the load is given an initial disturbance. The results from the simulations show that the fuzzy controller is capable of keeping the load-oscillation angles small throughout the maneuvers while completing the maneuvers in relatively reasonable times.

scholarly journals Sensor-less Brushed DC Motor Speed Control with Intelligent Controllers

2021 ◽  
Vol 20 ◽  
pp. 140-148
Author(s):  
Amir Salmaninejad ◽  
Rene V. Mayorga
Keyword(s):  
Closed Loop ◽  
Fuzzy Logic Controller ◽  
Fuzzy Inference ◽  
Mechanical Load ◽  
Dc Motor ◽  
Closed Loop Control ◽  
Motor Speed ◽  
Motor Shaft ◽  
Loop Control ◽  
Intelligent Controllers

A Direct Current (DC) Motor is usually supposed to be operated at a desired speed even if the load on the shaft is exposed to changes. One of its applications is in automatic door controllers like elevator automatic door drivers. Initially, to achieve this aim, a closed loop control can be applied. The speed feedback is usually prepared by a sensor (encoder or tachometer) coupled to the motor shaft. Most of these sensors do not always perform well, especially in elevator systems, where high levels of noise, physical tensions of the mobile car, and maintenance technicians walking on the car, make this environment too noisy. This Paper presents a new approach for precise closed loop control of the DC motor speed without a feedback sensor, while the output load is variable. The speed here is estimated by the Back EMF (BEMF) voltage obtained from the armature current. First, it is shown that a PID controller cannot control this process alone, and then intelligent controllers, Fuzzy Logic Controller (FLC) and Adaptive Neuro Fuzzy Inference Systems (ANFIS), assisting PID are applied to control this process. Finally, these controllers’ performance subjected to a variable mechanical load on the motor shaft are compared.

Hybrid Anti-Windup Fuzzy PI Controller Based Direct Torque Control of Three Phase Induction Motor

2014 ◽  
Vol 573 ◽  
pp. 155-160
Author(s):  
A. Pandian ◽  
R. Dhanasekaran
Keyword(s):  
Fuzzy Logic ◽  
Induction Motor ◽  
Fuzzy Logic Controller ◽  
Control Method ◽  
Fuzzy Controller ◽  
Direct Torque Control ◽  
Operating Conditions ◽  
Torque Control ◽  
Constant Speed ◽  
Three Phase

This paper presents improved Fuzzy Logic Controller (FLC) of the Direct Torque Control (DTC) of Three-Phase Induction Motor (IM) for high performance and torque control industrial drive applications. The performance of the IM using PI Controllers and general fuzzy controllers are meager level under load disturbances and transient conditions. The FLC is extended to have a less computational burden which makes it suitable for real time implementation particularly at constant speed and torque disturbance operating conditions. Hybrid control has advantage of integrating a superiority of two or more control techniques for better control performances. A fuzzy controller offers better speed responses for startup and large speed errors. If the nature of the load torque is varied, the steady state speed error of DTC based IM drive with fuzzy logic controller becomes significant. To improve the performance of the system, a new control method, Hybrid fuzzy PI control is proposed. The effectiveness of proposed method is verified by simulation based on MATLAB. The proposed Hybrid fuzzy controller has adaptive control over load toque variation and can maintain constant speed.

Fuzzy logic controller for a retrofitted closed-loop injection moulding machine

2000 ◽  
Vol 214 (1) ◽  
pp. 9-22 ◽  
Author(s):  
S-J Huang ◽  
T-H Lee
Keyword(s):  
Injection Moulding ◽  
Closed Loop ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Open Loop ◽  
Compression Phase ◽  
Loop Control ◽  
Injection Speed ◽  
Moulding Machine ◽  
Filling Phase

For the purposes of producing precise products and providing the flexibility for products variation, an open-loop control commercial injection moulding machine is retrofitted into a closed-loop control system for monitoring the filling and post-filling phases of the injection processes. The hydraulic control unit, control and interface circuits, safety limit switches and personal-computer-based controller were redesigned and constructed. Since the injection moulding processes have complicated non-linear dynamics and model uncertainty, the application of a classical proportional-integral-derivative controller has adaptivity and robustness problems, especially with regards to the pressure control during compression phase. Here, an intelligent fuzzy controller is employed to adjust the injection speed of the filling phase and to control the nozzle pressure of the post-filling phase. The experimental results show that this controller has good performance in actual injection moulding processes.

Design of a Hybrid Adaptive Neuro Fuzzy Inference System (ANFIS) Controller for Position and Angle Control of Inverted Pendulum (IP) Systems

Fuzzy Systems ◽  
2017 ◽  
pp. 308-320
Author(s):  
Ashwani Kharola
Keyword(s):  
Fuzzy Logic ◽  
Inverted Pendulum ◽  
Fuzzy Logic Controller ◽  
Fuzzy Inference ◽  
Fuzzy Controller ◽  
Data Sets ◽  
Inference System ◽  
Simulink Model ◽  
Neuro Fuzzy ◽  
Proposed Model

This paper illustrates a comparison study of Fuzzy and ANFIS Controller for Inverted Pendulum systems. IP belongs to a class of highly non-linear, unstable and multi-variable systems which act as a testing bed for many complex systems. Initially, a Matlab-Simulink model of IP system was proposed. Secondly, a Fuzzy logic controller was designed using Mamdani inference system for control of proposed model. The data sets from fuzzy controller was used for development of a Hybrid Sugeno ANFIS controller. The results shows that ANFIS controller provides better results in terms of Performance parameters including Settling time(sec), maximum overshoot(degree) and steady state error.

scholarly journals Frequency stabilization using fuzzy logic based controller for multi-area power system

2007 ◽  
Vol 25 (1) ◽  
pp. 22 ◽  
Author(s):  
H.D. Mathur ◽  
H.V. Manjunath
Keyword(s):  
Fuzzy Logic ◽  
Power System ◽  
Fuzzy Logic Controller ◽  
Fuzzy Inference ◽  
Fuzzy Controller ◽  
Frequency Control ◽  
Electrical Power ◽  
Load Frequency Control ◽  
System Response ◽  
Electrical Power System

In this paper, a fuzzy logic controller is proposed for load frequency control problem of electrical power system. The fuzzy controller is constructed as a set of control rules and the control signal is directly deduced from the knowledge base and the fuzzy inference. The study has been designed for a two area interconnected power system. A comparison among a conventional proportional integral (PI) controller, some other fuzzy gain scheduling controllers and the proposed fuzzy controller is presented and it has been shown that proposed controller can generate the best dynamic response following a step load change. Robustness of proposed controller is achieved by analyzing the system response with varying system parameters.

A Comparative Analysis of Integrated Boost Flyback Converter using PID and Fuzzy Controller

2015 ◽  
Vol 5 (4) ◽  
pp. 486
Author(s):  
R.Samuel Rajesh Babu
Keyword(s):  
Fuzzy Logic ◽  
Comparative Analysis ◽  
Pid Controller ◽  
Closed Loop ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Energy System ◽  
Flyback Converter ◽  
Integrated Boost ◽  
Simulation Results

<div class="Section1"><p class="papertitle">This paper presents a comparative analysis of Integrated boost flyback converter for Renewable energy System. IBFC is the combination of boost converter and fly back converter. The proposed converter is simulated in open and closed loop using PID and FUZZY controller. The Fuzzy Logic Controller (FLC) is used reduce the rise time, settling time to almost negligible and try to remove the delay time and inverted response. The performance of IBFC with fuzzy logic controller  is found better instead of PID controller. The simulation results are verified experimentally and  the output of converter is free from ripples and has regulated output voltage.</p></div>

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