scholarly journals Adaptive Fuzzy Command Filtered Control for Chua’s Chaotic System

2018 ◽  
Vol 2018 ◽  
pp. 1-10
Author(s):  
Lin Wang ◽  
Hui Wei ◽  
Chunzhi Yang
Keyword(s):  
Chaotic System ◽  
External Disturbance ◽  
Design Procedure ◽  
Small Region ◽  
Simulation Studies ◽  
Fuzzy Logic Systems ◽  
Tracking Errors ◽  
Adaptive Fuzzy ◽  
Lyapunov Stability Criterion ◽  
Derivatives Of

In this paper, we propose the command filtered adaptive fuzzy backstepping control (AFBC) approach for Chua’s chaotic system with external disturbance. Based on two proposed first-order command filters, the convergence of tracking errors as well as the problem of “explosion of complexity” in traditional backstepping design procedure is solved. In the command filtered AFBC design, we do not need to calculate the complicated partial derivatives of the virtual control inputs. Fuzzy logic systems (FLSs) are used to identify the system uncertainties in real time. Based on Lyapunov stability criterion, the proposed controller can guarantee that all signals in the closed-loop system keep bounded, and the tracking errors converge to a small region eventually. Finally, simulation studies have been provided to verify the effectiveness of the proposed method.

scholarly journals Adaptive Fuzzy Synchronization of Fractional-Order Chaotic Neural Networks with Backlash-Like Hysteresis

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Wenqing Fu ◽  
Heng Liu
Keyword(s):  
Neural Networks ◽  
Fractional Order ◽  
Control Method ◽  
Fuzzy Controller ◽  
Small Region ◽  
Fuzzy Logic Systems ◽  
Chaotic Neural Networks ◽  
Adaptive Fuzzy ◽  
Synchronization Errors ◽  
Lyapunov Stability Criterion

An adaptive fuzzy synchronization controller is designed for a class of fractional-order neural networks (FONNs) subject to backlash-like hysteresis input. Fuzzy logic systems are used to approximate the system uncertainties as well as the unknown terms of the backlash-like hysteresis. An adaptive fuzzy controller, which can guarantee the synchronization errors tend to an arbitrary small region, is given. The stability of the closed-loop system is rigorously analyzed based on fractional Lyapunov stability criterion. Fractional adaptation laws are established to update the fuzzy parameters. Finally, some simulation examples are provided to indicate the effectiveness and the robust of the proposed control method.

scholarly journals Adaptive fuzzy tracking control for a constrained flexible air-breathing hypersonic vehicle based on actuator compensation

2016 ◽  
Vol 13 (6) ◽  
pp. 172988141667111 ◽  
Author(s):  
Peng Fei Wang ◽  
Jie Wang ◽  
Xiang Wei Bu ◽  
Ying Jie Jia
Keyword(s):  
Tracking Control ◽  
Hypersonic Vehicle ◽  
Reference Trajectory ◽  
Fuzzy Logic Systems ◽  
Tracking Errors ◽  
Control Laws ◽  
Air Breathing ◽  
Adaptive Fuzzy ◽  
Adaptive Parameter ◽  
Actuator Constraints

The design of an adaptive fuzzy tracking control for a flexible air-breathing hypersonic vehicle with actuator constraints is discussed. Based on functional decomposition methodology, velocity and altitude controllers are designed. Fuzzy logic systems are applied to approximate the lumped uncertainty of each subsystem of air-breathing hypersonic vehicle model. Every controllers contain only one adaptive parameter that needs to be updated online with a minimal-learning-parameter scheme. The back-stepping design is not demanded by converting the altitude subsystem into the normal output-feedback formulation, which predigests the design of a controller. The special contribution is that novel auxiliary systems are developed to compensate both the tracking errors and desired control laws, based on which the explored controller can still provide effective tracking of velocity and altitude commands when the inputs are saturated. Finally, reference trajectory tracking simulation shows the effectiveness of the proposed method in its application to air-breathing hypersonic vehicle control.

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 Adaptive Fuzzy Synchronization of Fractional-Order Chaotic (Hyperchaotic) Systems with Input Saturation and Unknown Parameters

Complexity ◽  
2017 ◽  
Vol 2017 ◽  
pp. 1-16 ◽  
Author(s):  
Heng Liu ◽  
Ye Chen ◽  
Guanjun Li ◽  
Wei Xiang ◽  
Guangkui Xu
Keyword(s):  
Fractional Order ◽  
Control Method ◽  
External Disturbance ◽  
Input Saturation ◽  
Adaptive Fuzzy Control ◽  
Adaptive Controller ◽  
Unknown Parameters ◽  
Fuzzy Logic Systems ◽  
Adaptive Fuzzy ◽  
Hyperchaotic Systems

We investigate the synchronization problem of fractional-order chaotic systems with input saturation and unknown external disturbance by means of adaptive fuzzy control. An adaptive controller, accompanied with fractional adaptation law, is established, fuzzy logic systems are used to approximate the unknown nonlinear functions, and the fractional Lyapunov stability theorem is used to analyze the stability. This control method can realize the synchronization of two fractional-order chaotic or hyperchaotic systems and the synchronization error tends to zero asymptotically. Finally, we show the effectiveness of the proposed method by two simulation examples.

scholarly journals Composite Adaptive Fuzzy Prescribed Performance Control of Nonlinear Systems

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Xudong Cao ◽  
Jianjun Wang ◽  
Wei Xiang
Keyword(s):  
Nonlinear Systems ◽  
Initial Conditions ◽  
Performance Bounds ◽  
Fuzzy Logic Systems ◽  
Tracking Errors ◽  
Performance Control ◽  
Prescribed Performance ◽  
Adaptive Fuzzy ◽  
Prescribed Performance Control ◽  
Adaptation Law

This paper proposes an adaptive fuzzy prescribed performance control (PPC) method of a class of uncertain nonlinear systems. Different from the traditional PPC approach that requires the exact values of the initial conditions, by using a new type of performance function, the proposed PPC scheme together with a composite adaptation law works effectively even without the knowledge of initial conditions. Meanwhile, the constructed disturbance observer and fuzzy logic systems can estimate system uncertainties including external disturbances and fuzzy approximation errors. Under the proposed tracking controller, the boundedness of all involved signals is guaranteed, and the tracking errors satisfy the prescribed performance bounds all the time. Finally, simulation results show the efficacy of the proposed method.

scholarly journals Adaptive Fuzzy Robust Control for a Class of Nonlinear Systems via Small Gain Theorem

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Xingjian Wang ◽  
Shaoping Wang
Keyword(s):  
Adaptive Control ◽  
Robust Control ◽  
Nonlinear Systems ◽  
Closed Loop ◽  
Design Procedure ◽  
Control Law ◽  
Fuzzy Logic Systems ◽  
Adaptive Fuzzy ◽  
Small Gain Theorem ◽  
Small Gain

Practical nonlinear systems can usually be represented by partly linearizable models with unknown nonlinearities and external disturbances. Based on this consideration, we propose a novel adaptive fuzzy robust control (AFRC) algorithm for such systems. The AFRC effectively combines techniques of adaptive control and fuzzy control, and it improves the performance by retaining the advantages of both methods. The linearizable part will be linearly parameterized with unknown but constant parameters, and the discontinuous-projection-based adaptive control law is used to compensate these parts. The Takagi-Sugeno fuzzy logic systems are used to approximate unknown nonlinearities. Robust control law ensures the robustness of closed-loop control system. A systematic design procedure of the AFRC algorithm by combining the backstepping technique and small-gain approach is presented. Then the closed-loop stability is studied by using small gain theorem, and the result indicates that the closed-loop system is semiglobally uniformly ultimately bounded.

scholarly journals Adaptive Synchronization for Uncertain Delayed Fractional-Order Hopfield Neural Networks via Fractional-Order Sliding Mode Control

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Bo Meng ◽  
Xiaohong Wang
Keyword(s):  
Neural Networks ◽  
Fractional Order ◽  
Sliding Mode ◽  
Small Region ◽  
Hopfield Neural Networks ◽  
Adaptive Synchronization ◽  
Unknown Parameters ◽  
External Disturbances ◽  
Lyapunov Stability Criterion ◽  
Order Extension

Adaptive synchronization for a class of uncertain delayed fractional-order Hopfield neural networks (FOHNNs) with external disturbances is addressed in this paper. For the unknown parameters and external disturbances of the delayed FOHNNs, some adaptive estimations are designed. Firstly, a fractional-order switched sliding surface is proposed for the delayed FOHNNs. Then, according to the fractional-order extension of the Lyapunov stability criterion, a fractional-order sliding mode controller is constructed to guarantee that the synchronization error of the two uncertain delayed FOHNNs converges to an arbitrary small region of the origin. Finally, a numerical example of two-dimensional uncertain delayed FOHNNs is given to verify the effectiveness of the proposed method.

scholarly journals Direct adaptive fuzzy-neural control of unknown chaotic system

2004 ◽  
Vol 53 (12) ◽  
pp. 4087
Author(s):  
Tan Wen ◽  
Wang Yao－Nan
Keyword(s):  
Chaotic System ◽  
Neural Control ◽  
Adaptive Fuzzy ◽  
Fuzzy Neural

scholarly journals Data-driven automatic parking constrained control for four-wheeled mobile vehicles

2016 ◽  
Vol 13 (6) ◽  
pp. 172988141666366 ◽  
Author(s):  
Wenxu Yan ◽  
Jing Deng ◽  
Dezhi Xu
Keyword(s):  
Orientation Angle ◽  
Design Procedure ◽  
Data Driven ◽  
Control Input ◽  
Constrained Control ◽  
Tracking Errors ◽  
Rapid Responses ◽  
Control Scheme ◽  
Lyapunov Stability Analysis ◽  
Automatic Parking

In this article, a novel data-driven constrained control scheme is proposed for automatic parking systems. The design of the proposed scheme only depends on the steering angle and the orientation angle of the car, and it does not involve any model information of the car. Therefore, the proposed scheme-based automatic parking system is applicable to different kinds of cars. In order to further reduce the desired trajectory coordinate tracking errors, a coordinates compensation algorithm is also proposed. In the design procedure of the controller, a novel dynamic anti-windup compensator is used to deal with the change magnitude and rate saturations of automatic parking control input. It is theoretically proven that all the signals in the closed-loop system are uniformly ultimately bounded based on Lyapunov stability analysis method. Finally, a simulation comparison among the proposed scheme with coordinates compensation and Proportion Integration Differentiation (PID) control algorithm is given. It is shown that the proposed scheme with coordinates compensation has smaller tracking errors and more rapid responses than PID scheme.

STABILIZATION OF CHAOTIC SYSTEMS USING LINEAR SAMPLED-DATA CONTROLLER

2007 ◽  
Vol 17 (06) ◽  
pp. 2021-2031 ◽  
Author(s):  
H. K. LAM ◽  
F. H. F. LEUNG
Keyword(s):  
Chaotic System ◽  
Chaotic Systems ◽  
Lorenz System ◽  
Design Procedure ◽  
Sampling Period ◽  
Feedback Gain ◽  
Sampled Data ◽  
Lyapunov Approach ◽  
And Performance ◽  
Data Controller

This paper proposes a linear sampled-data controller for the stabilization of chaotic system. The system stabilization and performance issues will be investigated. Stability conditions will be derived based on the Lyapunov approach. The findings of the maximum sampling period and the feedback gain of controller, and the optimization of system performance will be formulated as a generalized eigenvalue minimization problem. Based on the analysis result, a stable linear sampled-data controller can be realized systematically to stabilize a chaotic system. An example of stabilizing a Lorenz system will be given to illustrate the design procedure and effectiveness of the proposed approach.

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