Type-2 Fuzzy Controller with Type-1 Tuning Scheme for Overhead Crane Control

2017 ◽  
pp. 567-576 ◽  
Author(s):  
Indrajıt Naskar ◽  
A. K. Pal
Keyword(s):  
Fuzzy Controller ◽  
Overhead Crane ◽  
Crane Control ◽  
Tuning Scheme

Interval Type-2 Fuzzy Logic Control of NM70 Shape Memory Actuator

2014 ◽  
Author(s):  
Ireneusz Dominik
Keyword(s):  
Fuzzy Logic ◽  
Shape Memory ◽  
Fuzzy Logic Control ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Logic Control ◽  
Interval Type ◽  
Nonlinear Plant

The main aim of this article is to present the usage of type-2 fuzzy logic controller to control a shape memory actuator. To enhance real-time performance simplified interval fuzzy sets were used. The algorithm was implemented in the ATmega32 microcontroller. The dedicated PC application was also built. The fuzzy logic controller type-2 was tested experimentally by controlling position of the shape memory alloy actuator NM70 which despite its small size distinguishes itself by its strength. The obtained results confirmed that type-2 fuzzy controller performed efficiently with a difficult to control nonlinear plant. The research also proved that interval type-2 controllers, which are a simplified version of the general type-2 controllers, are very efficient. They can handle uncertainties without increasing drastically the computational complexity. Experimental data comparison of the fuzzy logic controller type-2 with type-1 clearly indicates the superiority of the former, especially in reducing overshooting.

Implementation of the Type-2 Fuzzy Controller in PLC

2010 ◽  
Vol 164 ◽  
pp. 95-98 ◽  
Author(s):  
Ireneusz Dominik
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Research Work ◽  
Problem Type ◽  
Object A ◽  
Develop Type ◽  
Linear Object

The main aim of the presented research work was to develop type-2 fuzzy logic controller, which by its own design should be “more intelligent” than type-1. Along with the intelligence it should provide better results in solving a particular problem. Type-2 fuzzy logic controller is not well-known and it is rarely used at present. The idea of type-2 fuzzy logic set was presented by Zadeh in 1975, shortly after the presentation of type-1 fuzzy set. At the beginning scientists and researchers worked on type-1. Only after developing type-1 the attention was directed towards the type-2. The first applications of type-2 fuzzy logic in control appeared in 2003. The fuzzy logic controller type-2 was tested experimentally by controlling a non-linear object: a shape memory alloy (SMA) actuator DM-01PL, made by Miga Motor company, which despite small size distinguishes itself by its 9 N strength. Comparison of experimental data of the fuzzy logic controller type-2 and type-1 clearly indicates the superiority of the former, particularly in reducing signal overshoots.

Simplified architecture of a type-2 fuzzy controller using four embedded type-1 fuzzy controllers and its application to a greenhouse climate control system

2009 ◽  
Vol 223 (5) ◽  
pp. 619-631 ◽  
Author(s):  
I A Hameed
Keyword(s):  
Control System ◽  
Control Systems ◽  
Degrees Of Freedom ◽  
Fuzzy Controller ◽  
Climate Control ◽  
Fuzzy Logic Systems ◽  
Greenhouse Climate ◽  
Greenhouse Climate Control

Uncertainty is an inherent part of control systems used in real-world applications. The use of new methods for handling incomplete information and to cope with large amounts of uncertainties is of fundamental importance. The traditional type-1 fuzzy sets (T1FSs) used in conventional fuzzy logic systems (FLSs) cannot fully handle the uncertainties present in control systems. The type-2 FSs (T2FSs) used in T2FLSs can handle such uncertainties in a better way because they provide more parameters and more degrees of freedom. In spite of the features of the T2FS, it has not received the attention it deserves because of its implementation complexity. In this paper, a simple architecture of the T2FLS using four embedded T1FLSs is introduced. The performance of the proposed T2FLS is assessed by applying it to a multi-input multi-output (MIMO) greenhouse climate control system. Simulation results showed that the simplified architecture is able to cope with the complexity of the plant and has the ability to handle measurement and modelling uncertainties. The performance of the proposed T2FLS is comparable with the computationally costly T2FLS and outperforms its traditional T1FLS counterpart.

ON THE CONTROL OF TUMOR GROWTH VIA TYPE-1 AND INTERVAL TYPE-2 FUZZY LOGIC

2015 ◽  
Vol 15 (05) ◽  
pp. 1550083 ◽  
Author(s):  
SHAHRZAD GHOLAMI ◽  
ARIA ALASTY ◽  
HASSAN SALARIEH ◽  
MEHDI HOSSEINIAN-SARAJEHLOU
Keyword(s):  
Fuzzy Logic ◽  
Tumor Growth ◽  
Cancer Cells ◽  
Fuzzy Controller ◽  
Growth Control ◽  
Uncertain Information ◽  
Fuzzy Logic Systems ◽  
Interval Type

This paper deals with growth control of cancer cells population using type-1 and interval type-2 fuzzy logic. A type-1 fuzzy controller is designed in order to reduce the population of cancer cells, adjust the drug dosage in a manner that allows normal cells re-grow in treatment period and maintain the maximum drug delivery rate and plasma concentration of drug in an appropriate range. Two different approaches are studied. One deals with reducing the number of cancer cells without any concern about the rate of decreasing, and the other takes the rate of malignant cells damage into consideration. Due to the fact that uncertainty is an inherent part of real systems and affects controller efficacy, employing new methods of design such as interval type-2 fuzzy logic systems for handling uncertainties may be efficacious. Influence of noise on the system is investigated and the effect of altering free parameters of design is studied. Using an interval type-2 controller can diminish the effects of incomplete and uncertain information about the system, environmental noises, instrumentation errors, etc. Simulation results confirm the effectiveness of the proposed methods on tumor growth control.

Type-2 fuzzy control for line following using line detection images

2020 ◽  
Vol 39 (5) ◽  
pp. 6089-6097
Author(s):  
Oscar Castillo ◽  
Prometeo Cortés-Antonio ◽  
Patricia Melin ◽  
Fevrier Valdez
Keyword(s):  
Comparative Analysis ◽  
Control Systems ◽  
Fuzzy Controller ◽  
Line Detection ◽  
Omnidirectional Mobile Robot ◽  
Adaptive Parameters ◽  
Control Schemes ◽  
Line Following

This work presents a comparative analysis of Type-1 and Type-2 fuzzy controllers to drive an omnidirectional mobile robot in line-following tasks using line detection images. Image processing uses a Prewitt filter for edge detection and determines the error from the line location. The control systems are tested using four different paths from the Robotino® SIM simulator. Also, two different strategies in the design and implementation of the controllers are presented. In the first one, a PD controller scheme is extended by using a fuzzy system to have adaptive parameters P and D, additionally, Type-2 Fuzzy sets are used to give robustness to the controller. In the second case, a Fuzzy controller is designed to compute in a direct way the control variables and it is extended to Type-2 Fuzzy controller. Finally, experimental results and comparative analysis are presented for the five control schemes by comparing the running time and the standard deviation to measure the robustness of the control systems.

Semi-active seismic control of an 11-DOF building model with TMD+MR damper using type-1 and -2 fuzzy algorithms

2017 ◽  
Vol 24 (13) ◽  
pp. 2938-2953 ◽  
Author(s):  
Akbar Bathaei ◽  
Seyed Mehdi Zahrai ◽  
Meysam Ramezani
Keyword(s):  
Active Control ◽  
Structural Damage ◽  
Structural Control ◽  
Passive Control ◽  
Fuzzy Controller ◽  
Mr Damper ◽  
Control Force ◽  
Building Model

Nowadays, vibration control of structures is considered as a challenging field among scientists and engineers. Structural damage and financial losses due to recent earthquakes in different countries have more than ever before accentuated the importance of controlling earthquake-induced vibrations. In recent years, semi-active control has been introduced as an efficient and reliable type of structural control which provides the reliability of passive control and flexibility of active control systems at the same time. In this study, the performance of a semi-active tuned mass damper (TMD) with adaptive magnetorheological (MR) damper is investigated using type-1 and -2 fuzzy controllers for seismic vibration mitigation of an 11-degree of freedom building model. The TMD is installed on the roof and the MR damper is located on the 11th story. The MR damper has a capacity of producing a 1000 kN control force. The fuzzy system is designed based on the acceleration and velocity of the top floor determining the input voltage needed to produce the control force based on accelerating or decelerating movements of structure. The seismic performance of semi-active type-2 controller, which considers the uncertainties related to input variables, is higher than that of the type-1 fuzzy controller. The type-2 fuzzy controller is capable of reducing further the maximum displacement, acceleration, and base shear of the structure by 11.7, 14, and 11.2%, respectively, compared to the type-1 fuzzy controller.

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