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.

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.

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.

scholarly journals Adaptive Fuzzy Control for Stochastic Pure-Feedback Nonlinear Systems with Unknown Hysteresis and External Disturbance

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-11
Author(s):  
Xikui Liu ◽  
Yingying Ge ◽  
Yan Li
Keyword(s):  
Nonlinear Systems ◽  
Fuzzy Control ◽  
External Disturbance ◽  
Tracking Error ◽  
Adaptive Fuzzy Control ◽  
Nonlinear Function ◽  
Small Neighborhood ◽  
Mean Value Theorem ◽  
Adaptive Fuzzy ◽  
Control Scheme

This paper solves the tracking control problem of a class of stochastic pure-feedback nonlinear systems with external disturbances and unknown hysteresis. By using the mean-value theorem, the problem of pure-feedback nonlinear function is solved. The direction-unknown hysteresis problem is solved with the aid of the Nussbaum function. The external disturbance problems can be solved by defining new Lyapunov functions. Using the backstepping technique, a new adaptive fuzzy control scheme is proposed. The results show that the proposed control scheme ensures that all signals of the closed-loop system are semiglobally uniformly bounded and the tracking error converges to the small neighborhood of origin in the sense of mean quartic value. Simulation results illustrate the effectiveness of the proposed control scheme.

Adaptive Fuzzy Tracking Control for Stochastic Nonlinear Systems with Time-Varying Input Delays Using the Quadratic Functions

2018 ◽  
Vol 26 (01) ◽  
pp. 109-142 ◽  
Author(s):  
Hongyun Yue ◽  
Junmin Li ◽  
Jiarong Shi ◽  
Wei Yang
Keyword(s):  
Nonlinear Systems ◽  
Tracking Error ◽  
Adaptive Fuzzy Control ◽  
Design Procedure ◽  
Quadratic Functions ◽  
Input Delay ◽  
Stochastic Nonlinear Systems ◽  
Fourth Moment ◽  
Time Varying ◽  
Adaptive Fuzzy

In this paper, for the stochastic nonlinear systems the adaptive fuzzy tracking controllers are constructed by using the fuzzy logic systems (FLS) and the classical quadratic functions. Compared with the existing results for adaptive fuzzy control, the stochastic nonlinear systems investigated in this paper are much more complex since the systems not only have distributed state time-varying delays in the noise jamming intensity terms but also have the time-varying delays in the input signals. During the controller design procedure, through appropriate assumptions and a state transformation the system with time-varying input delay can be easily transformed into a system without input delay. The other main advantage is that quadratic functions are used as Lyapunov functions to analyze the stability of systems, other than the fourth moment approach proposed by H. Deng and M. Krstic, and the hyperbolic tangent functions are introduced to deal with the Hessian terms. The proposed adaptive fuzzy controller guarantees that all the signals in the closed-loop system are bounded in probability and the tracking error can converge to a small residual set around the origin in the mean square sense.

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.

scholarly journals Damping Force Tracking Control of MR Damper System Using a New Direct Adaptive Fuzzy Controller

2015 ◽  
Vol 2015 ◽  
pp. 1-16 ◽  
Author(s):  
Xuan Phu Do ◽  
Kruti Shah ◽  
Seung-Bok Choi
Keyword(s):  
Vibration Control ◽  
Tracking Control ◽  
Fuzzy Controller ◽  
Tracking Error ◽  
Mr Damper ◽  
Control Performance ◽  
Damping Force ◽  
Adaptive Fuzzy Controller ◽  
Adaptive Fuzzy ◽  
Force Tracking

This paper presents a new direct adaptive fuzzy controller and its effectiveness is verified by investigating the damping force tracking control of magnetorheological (MR) fluid based damper (MR damper in short) system. In the formulation of the proposed controller, a model of interval type 2 fuzzy controller is combined with the direct adaptive control to achieve high performance in vibration control. In addition,H∞(Hinfinity) tracking technique is used in building a model of the direct adaptive fuzzy controller in which an enhanced iterative algorithm is combined with the fuzzy model. After establishing a closed-loop control structure to achieve high control performance, a cylindrical MR damper is adopted and damping force tracking results are obtained and discussed. In addition, in order to demonstrate the effectiveness of the proposed control strategy, two existing controllers are modified and tested for comparative work. It has been demonstrated from simulation and experiment that the proposed control scheme provides much better control performance in terms of damping force tracking error. This leads to excellent vibration control performance of the semiactive MR damper system associated with the proposed controller.

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