scholarly journals Adaptive Fuzzy Control of Uncertain Robotic Manipulator

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Jinglei Zhou ◽  
Qunli Zhang
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Controller ◽  
Mimo System ◽  
Lagrange Equation ◽  
Multiple Input Multiple Output ◽  
Adaptive Fuzzy Control ◽  
Robotic Manipulator ◽  
Fuzzy Logic Systems ◽  
Adaptive Fuzzy ◽  
Adaptive Fuzzy Logic

This paper designs a kind of adaptive fuzzy controller for robotic manipulator considering external disturbances and modeling errors. First, n-link uncertain robotic manipulator dynamics based on the Lagrange equation is changed into a two-order multiple-input multiple-output (MIMO) system via feedback technique. Then, an adaptive fuzzy logic control scheme is studied by using sliding theory, which adopts the adaptive fuzzy logic systems to estimate the uncertainties and employs a filtered error to make up for the approximation errors, hence enhancing the robust performance of robotic manipulator system uncertainties. It is proved that the tracking errors converge into zero asymptotically by using Lyapunov stability theory. Last, we take a two-link rigid robotic manipulator as an example and give its simulations. Compared with the existing results in the literature, the proposed controller shows higher precision and stronger robustness.

Output Stable Control Design for a Class of Nonlinear Systems Based on Adaptive Fuzzy Logic Systems

2014 ◽  
Vol 945-949 ◽  
pp. 2670-2675
Author(s):  
Zi Lin Gao ◽  
Yong Pan ◽  
Jiang Xiong ◽  
Jin Peng Chen
Keyword(s):  
Fuzzy Logic ◽  
Nonlinear Systems ◽  
Approximation Property ◽  
Control Design ◽  
Universal Approximation ◽  
Fuzzy Logic Systems ◽  
Adaptive Fuzzy ◽  
Adaptive Fuzzy Logic ◽  
Logic Systems ◽  
Stable Control

The adaptive fuzzy logic systems are constructed in this paper by utilizing the data information sampled from the inputs and outputs of unknown functions in the nonlinear systems controlled, and then output stable controller is synthesized for a class of uncertain nonlinear systems based on the universal approximation property of adaptive fuzzy logic systems. Finally, the simulation shows the validity of the method in this paper.

Self Tuning Based Adaptive Fuzzy Logic Controller in Lab view for Sterilizing Equipments

2014 ◽  
Vol 3 (2) ◽  
pp. 84
Author(s):  
P. J. Ragu
Keyword(s):  
Fuzzy Logic ◽  
Temperature Control ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Adaptive Fuzzy ◽  
Lab View ◽  
Adaptive Fuzzy Logic ◽  
Self Tuning ◽  
Input Variables ◽  
Temperature Errors

In this paper, temperature monitoring of sterilizing equipment system was established with the help of fuzzy and self tuning Adaptive fuzzy logic controller designed in Lab VIEW software. It combines the advantages of both fuzzy logic and self tuning Adaptive fuzzy logic controller. The implementation attempts to rectify the errors between the measured value and the set point which helps to achieve efficient temperature control. The Adaptive fuzzy controller uses defined rules to control the system based on the current values of input variables and temperature errors. The simulation results presented in order to evaluate the proposed method. The result shows that self tuning  Adaptive fuzzy logic controller was tolerant to disturbance and the temperature control is most accurate.

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.

scholarly journals Design and Study of an Adaptive Fuzzy Logic-Based Controller for Wheeled Mobile Robots Implemented in the Leader-Follower Formation Approach

2021 ◽  
Vol 11 (2) ◽  
pp. 6935-6942
Author(s):  
H. Medjoubi ◽  
A. Yassine ◽  
H. Abdelouahab
Keyword(s):  
Fuzzy Logic ◽  
Feedback Control ◽  
Tracking Control ◽  
Formation Control ◽  
Fuzzy Controller ◽  
Wheeled Mobile Robots ◽  
Trajectory Tracking Control ◽  
Adaptive Fuzzy ◽  
Logic Control ◽  
Adaptive Fuzzy Logic

This paper presents a new design of an adaptive fuzzy logic control by implementing the leader-follower approach. The principle is to modify the feedback control of non-holonomic Wheeled Mobile Robot (WMR) to be adaptive according to a fuzzy controller in the control loop, in order to adjust the feedback control gains according to the distance error between the reference path and the real position. The trajectory tracking control for a single WMR is extended to the formation control for two WMRs in which the first one is the leader and the second is the follower. Simulation results are presented to demonstrate the effectiveness of the proposed controller.

scholarly journals Adaptive Fuzzy Controller Design for Solar And Wind Based Hybrid System

2018 ◽  
Vol 7 (2.24) ◽  
pp. 283 ◽  
Author(s):  
M Rathaiah ◽  
P Ram Kishore Kumar Reddy ◽  
P Sujatha
Keyword(s):  
Fuzzy Logic ◽  
Renewable Energy ◽  
Hybrid System ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Renewable Energy Sources ◽  
Energy Sources ◽  
Solar Pv ◽  
Adaptive Fuzzy ◽  
Adaptive Fuzzy Logic

Renewable Energy Resources plays an active role in standing against   global warming and reduce the use of conventional energy sources. Hybrid systems formed by combining the renewable energy sources are efficient relatively. The intent of this paper is to furnish endurable power for frontier and far-off places with hybrid-system of architecture. The intended system embodying DFIG and solar PV based wind turbine. In solar systems, control mechanism is essential for improving the performance. This paper proposes a method of incremental conductance approach based MPPT Adaptive Fuzzy Logic Controller for grid connected PV system which is composed of a boost converter and a three phase inverter. Adaptive Fuzzy Logic Controller provides fast response and better %THD compared to Fuzzy and PI controllers. In solar system, MPPT will magnify solar output power value. The DFIG has two controllers Grid-Side Control (GSC) and Rotor-Side Control (RSC). The rated rotor speed and DC-link voltage are regulated by RSC and GSC through PI, Fuzzy Logic Controller and AFLC strategies. By using simulation studies performed by three control strategies, %THD analysis is carried out.  

Robust adaptive fuzzy sliding mode controller for nonlinear uncertain hysteretic systems

2020 ◽  
Vol 42 (13) ◽  
pp. 2519-2532
Author(s):  
Aissa Rebai ◽  
Kamel Guesmi
Keyword(s):  
Fuzzy Controller ◽  
Sliding Mode ◽  
Tracking Error ◽  
Adaptive Fuzzy Control ◽  
Control Technique ◽  
Fuzzy Logic Systems ◽  
Integral Control ◽  
Adaptive Fuzzy ◽  
Hysteretic Systems ◽  
Robust Adaptive

This paper deals with the problem of adaptive fuzzy control for a class of nonlinear uncertain systems with hysteresis input. Fuzzy logic systems are employed to approximate the unknown nonlinear behaviors, and the sliding mode technique is used to synthesize an adaptive fuzzy controller. A proportional integral control term is adopted to reduce the chattering phenomenon engendered by both sliding mode control technique and hysteretic characteristic of the system. The proposed control scheme ensures the boundedness of all closed-loop signals, and forces the tracking error to converge to zero. The main contribution of this work is the development of a control strategy for a class of nonlinear hysteretic systems subject to external disturbances and uncertainties. Two case studies are given to illustrate and to prove the effectiveness of the presented approach.

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