Adaptive Fuzzy Control of Tension Variations due to the Eccentric Unwinding Roll in Multi-Span Web Transport Systems

1999 ◽  
Author(s):  
Sungchul Jee ◽  
Sungchol Kim ◽  
Kee-Hyun Shin
Keyword(s):  
Real Time ◽  
Transport System ◽  
Pid Controller ◽  
Fuzzy Controller ◽  
Adaptive Fuzzy Control ◽  
Transport Systems ◽  
Adaptive Fuzzy Controller ◽  
Adaptive Fuzzy ◽  
Ac Motors ◽  
The Web

Abstract Disturbances due to the eccentric unwinding roll/roller can create significant tension variations in the web spans in multi-driven web transport systems. The drivers are interconnected by an elastic web material (a 14-micrometer thick Polypropylene film was used for this study). Specifically, eccentricity of an upstream roller such as an unwinding roll creates upstream tension variation, and the tension variation in upstream web spans is transported to downstream due to the interconnection between the web spans. However, it is not easy to obtain an accurate mathematical model of the web transport system, for the design of a tension controller, which contains several actuators, sensors, gears, bearing systems, and interconnected web spans. In this paper, an adaptive fuzzy controller which automatically tunes its parameters in real-time is suggested to regulate tension variations in multi-spans due to an eccentric unwinding roll. In the proposed method, the input and output ranges are adjusted together according to continuous observation of tension error and change in the error. The proposed controller is implemented on a prototype web transport system which consists of three AC motors, real-time target controllers, unwinding and winding rolls with two-spans of web including sensors for the measurement of tensions and speeds of the web. The Experimental results show that the proposed adaptive fuzzy controller successfully rejects the effects of the disturbances due to the eccentric unwinding roll and substantially reduces the tension variations in both web spans. The adaptive fuzzy controller outperformed the conventional PID controller as the frequency of the eccentricity disturbance increased.

Application Research on H∞ Optimization Control of Permanent Magnet Linear Servo System Based on Adaptive Fuzzy Control Strategy

2013 ◽  
Vol 694-697 ◽  
pp. 2185-2189
Author(s):  
Xiao Ping Zhu ◽  
Xiu Ping Wang ◽  
Chun Yu Qu ◽  
Jun You Zhao
Keyword(s):  
Fuzzy Control ◽  
Control Strategy ◽  
Control Method ◽  
Fuzzy Controller ◽  
External Disturbance ◽  
Adaptive Fuzzy Control ◽  
Servo System ◽  
Robust Controller ◽  
Adaptive Fuzzy Controller ◽  
Adaptive Fuzzy

In order to against the uncertain disturbance of AC linear servo system, an H mixed sensitivity control method based on adaptive fuzzy control was putted forward in the paper. The controller is comprised of an adaptive fuzzy controller and a H robust controller, the adaptive fuzzy controller is used to approximate this ideal control law, H robust controller is designed for attenuating the approximation errors and the influence of the external disturbance. The experimental results show that this control strategy not only has a strong robustness to uncertainties of the linear system, but also has a good tracking performance, furthermore the control greatly improves the robust tracking precision of the direct drive linear servo system.

Design of Adaptive Fuzzy Control for a Class of Networked Nonlinear Systems

2017 ◽  
Vol 139 (3) ◽  
Author(s):  
Mohamed Hamdy ◽  
Sameh Abd-Elhaleem ◽  
M. A. Fkirin
Keyword(s):  
Nonlinear Systems ◽  
Fuzzy Controller ◽  
External Disturbance ◽  
Tracking Error ◽  
Adaptive Fuzzy Control ◽  
Time Varying ◽  
Fuzzy Logic Systems ◽  
Packet Losses ◽  
Adaptive Fuzzy Controller ◽  
Adaptive Fuzzy

This paper presents an adaptive fuzzy controller for a class of unknown nonlinear systems over network. The network-induced delays can degrade the performance of the networked control systems (NCSs) and also can destabilize the system. Moreover, the seriousness of the delay problem is aggravated when packet losses occur during a transmission of data. The proposed controller uses a filtered tracking error to cope the time-varying network-induced delays. It is also robust enough to cope some packet losses in the system. Fuzzy logic systems (FLSs) are used to approximate the unknown nonlinear functions that appear in the tracking controller. Based on Lyapunov stability theory, the constructed controller is proved to be asymptotically stable. Stability of the adaptive fuzzy controller is guaranteed in the presence of bounded external disturbance, time-varying delays, and data packet dropouts. Simulated application of the inverted pendulum tracking illustrates the effectiveness of the proposed technique with comparative results.

Adaptive Fuzzy Controller Design Based on Aircraft Model

2014 ◽  
Vol 556-562 ◽  
pp. 2470-2473
Author(s):  
Yu Qing Li ◽  
Chong Lei
Keyword(s):  
Attitude Control ◽  
Fuzzy Controller ◽  
Controller Design ◽  
Adaptive Fuzzy Control ◽  
Simulation Method ◽  
Vehicle Performance ◽  
Adaptive Fuzzy Controller ◽  
Adaptive Fuzzy ◽  
Aircraft Model ◽  
Control Equation

According to the attitude control equation and the equations of fluid mechanics, build dynamic model .The system simulation method and the MATLAB software were used to study on the aircraft model for several different controller system, which including PID controller, T-S fuzzy controller, The adaptive fuzzy controller design. Analysis of interference signals on the performance of the aircraft control system, consider the overshoot, steady-state error, resistance to load disturbance and parameter changes adaptability, robustness. Finally, It is concluded that different controller of vehicle performance index, and then analysis from the advantages of adaptive fuzzy control in the aspect of aircraft model.

Research of Robust Adaptive Fuzzy Control in Manipulator

2011 ◽  
Vol 317-319 ◽  
pp. 713-717
Author(s):  
Hong Lin Li ◽  
Peng Bing Zhao
Keyword(s):  
Fuzzy Control ◽  
Influencing Factors ◽  
Fuzzy Controller ◽  
Adaptive Fuzzy Control ◽  
Random Disturbance ◽  
State Variables ◽  
Adaptive Fuzzy Controller ◽  
Adaptive Fuzzy ◽  
Load Variation ◽  
Robust Adaptive

There are friction characteristics, random disturbance, load variation and other nonlinear influencing factors in the multi-joint manipulator system generally. According to the problem that the traditional PID and fuzzy control are difficult to achieve rapid and high-precision control for this kind of system, a kind of robust adaptive fuzzy controller was designed based on fuzzy compensation under the circumstances that the fuzzy information can be known and all the state variables can be measured. Simultaneously, in order to reduce the computational load of fuzzy approximation and improve the efficiency of mathematical operation, a method that distinguishing different disturbance compensatory terms and approximating each of them respectively was adopted. The simulation results show that the robust adaptive fuzzy controller based on fuzzy compensation can restrain friction, disturbance, load variation and other nonlinear influencing factors.

scholarly journals The adaptive fuzzy designed PID controller using wavelet network

2009 ◽  
Vol 6 (2) ◽  
pp. 141-163 ◽  
Author(s):  
Emary El ◽  
Walid Emar ◽  
Musbah Aqel
Keyword(s):  
Fuzzy Logic ◽  
Adaptive Control ◽  
Pid Controller ◽  
Fuzzy Controller ◽  
Expert Knowledge ◽  
Wavelet Network ◽  
Fuzzy Adaptive Control ◽  
Adaptive Fuzzy Controller ◽  
Adaptive Fuzzy ◽  
Fuzzy Adaptive

During the past several years, fuzzy control has emerged as one of the most active and fruitful areas for research in the applications of the fuzzy set theory, especially in the realm of the industrial processes, which do not lend themselves to control by conventional methods because of a lack of quantitative data regarding the inputoutput relations i.e., accurate mathematical models. The fuzzy logic controller based on wavelet network provides a means of converting a linguistic control strategy based on expert knowledge into an automatic strategy. In the available literature, one can find scores of papers on fuzzy logic based controllers or fuzzy adaptation of PID controllers. However, relatively less number of papers is found on fuzzy adaptive control, which is not surprising since fuzzy adaptive control is relatively new tool in control engineering. In this paper, fuzzy adaptive PID controller with wavelet network is discussed in subsequent sections with simulations. An adaptive neural network structure was proposed. This structure was used to replace the linearization feedback of a second order system (plant, process). Also, in this paper, it is proposed that the controller be tuned using Adaptive fuzzy controller where Adaptive fuzzy controller is a stochastic global search method that emulates the process of natural evolution. It is shown that Adaptive fuzzy controller be capable of locating high performance areas in complex domains without experiencing the difficulties associated with high dimensionality or false optima as may occur with gradient decent techniques. From the output results, it was shown that Adaptive fuzzy controller gave fast convergence for the nonparametric function under consideration in comparison with conventional Neural Wavelet Network (NWN).

scholarly journals Heuristic Global Optimization of an Adaptive Fuzzy Controller for the Inverted Pendulum System: Experimental Comparison

2020 ◽  
Vol 10 (18) ◽  
pp. 6158
Author(s):  
Miguel Llama ◽  
Alejandro Flores ◽  
Ramon Garcia-Hernandez ◽  
Victor Santibañez
Keyword(s):  
Real Time ◽  
Inverted Pendulum ◽  
Fuzzy Controller ◽  
Parameter Tuning ◽  
Lyapunov Theory ◽  
Experimental Comparison ◽  
Pendulum System ◽  
Adaptive Fuzzy Controller ◽  
Adaptive Fuzzy ◽  
Inverted Pendulum System

In this paper an adaptive fuzzy controller is proposed to solve the trajectory tracking problem of the inverted pendulum on a cart system. The designed algorithm is featured by not using any knowledge of the dynamic model and incorporating a full-state feedback. The stability of the closed-loop system is proven via the Lyapunov theory, and boundedness of the solutions is guaranteed. The proposed controller is heuristically tuned and its performance is tested via simulation and real-time experimentation. For this reason, a tuning method is investigated via evolutionary algorithms: particle swarm optimization, firefly algorithm and differential evolution in order to optimize the performance and verify which technique produces better results. First, a model-based simulation is carried out to improve the parameter tuning of the fuzzy systems, and then the results are transferred to real-time experiments. The optimization procedure is presented as well as the experimental results, which are also discussed.

Adaptive fuzzy controller: Application to the control of the temperature of a dynamic room in real time

2006 ◽  
Vol 157 (16) ◽  
pp. 2241-2258 ◽  
Author(s):  
I. Rojas ◽  
H. Pomares ◽  
J. Gonzalez ◽  
L.J. Herrera ◽  
A. Guillen ◽  
...  
Keyword(s):  
Real Time ◽  
Fuzzy Controller ◽  
Adaptive Fuzzy Controller ◽  
Adaptive Fuzzy
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