scholarly journals Novel Fuzzy-Modeling-Based Adaptive Synchronization of Nonlinear Dynamic Systems

Complexity ◽  
2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Shih-Yu Li ◽  
Chin-Sheng Chen ◽  
Lap-Mou Tam ◽  
Shun-Hung Tsai
Keyword(s):  
Dynamic Systems ◽  
Fuzzy Controller ◽  
Fuzzy Model ◽  
Adaptive Synchronization ◽  
The Novel ◽  
Unknown Parameters ◽  
Synchronization Problem ◽  
Adaptive Control Strategy ◽  
Modeling Strategy ◽  
Synchronization Scheme

In this paper, a novel fuzzy-model-based adaptive synchronization scheme and its fuzzy update laws of parameters are proposed to address the adaptive synchronization problem. The proposed fuzzy controller does not share the same premise of fuzzy system, and the numbers of fuzzy controllers is reduced effectively through the novel modeling strategy. In addition, based on the adaptive synchronization scheme, the error dynamic system can be guaranteed to be asymptotically stable and the true values of unknown parameters can be obtained. Two identical complicated dynamic systems, Mathieu-Van der pol system (M-V system) with uncertainties, are illustrated for numerical simulation example to show the effectiveness and feasibility of the proposed novel adaptive control strategy.

Adaptive Synchronization of Chaotic Genesio–Tesi Systems Via A Nonlinear Control

2018 ◽  
Vol 7 (3.19) ◽  
pp. 136
Author(s):  
Esmat Sadat Alaviyan Shahri
Keyword(s):  
Nonlinear Control ◽  
Chaos Synchronization ◽  
Chaotic Systems ◽  
Adaptive Strategy ◽  
Adaptive Synchronization ◽  
Unknown Parameters ◽  
Control Effort ◽  
Analysis And Design ◽  
Synchronization Problem ◽  
Synchronization Scheme

The paper presents the stabilization and adaptive synchronization problem of a class of chaotic systems (Genesio–Tesi system) with three unknown parameters. A novel nonlinear control effort is proposed and an adaptive strategy is presented in order to the states of two Genesio–Tesi systems were asymptotically synchronized. The known Lyapunov method guarantees the presented stability analysis and design. An illustrative simulation result is given to demonstrate the effectiveness of the proposed chaos synchronization scheme.

NEURAL MODELING AND CONTROL OF DYNAMIC SYSTEMS WITH HYSTERESIS

2007 ◽  
Vol 31 (1) ◽  
pp. 127-141
Author(s):  
Yonghong Tan ◽  
Xinlong Zhao
Keyword(s):  
Dynamic Systems ◽  
Control Strategy ◽  
Neural Modeling ◽  
Modeling And Control ◽  
Control Scheme ◽  
The Neural Networks ◽  
Adaptive Control Strategy ◽  
Set Up ◽  
Modeling Strategy ◽  
And Control

A hysteretic operator is proposed to set up an expanded input space so as to transform the multi-valued mapping of hysteresis to a one-to-one mapping so that the neural networks can be applied to model of the behavior of hysteresis. Based on the proposed neural modeling strategy for hysteresis, a pseudo control scheme is developed to handle the control of nonlinear dynamic systems with hysteresis. A neural estimator is constructed to predict the system residual so that it avoids constructing the inverse model of hysteresis. Thus, the control strategy can be used for the case where the output of hysteresis is unmeasurable directly. Then, the corresponding adaptive control strategy is presented. The application of the novel modeling approach to hysteresis in a piezoelectric actuator is illustrated. Then a numerical example of using the proposed control strategy for a nonlinear system with hysteresis is presented.

scholarly journals Further results on robust fuzzy dynamic systems with LMI D-stability constraints

2014 ◽  
Vol 24 (4) ◽  
pp. 785-794 ◽  
Author(s):  
Wudhichai Assawinchaichote
Keyword(s):  
Dynamic Systems ◽  
Fuzzy Controller ◽  
Sufficient Conditions ◽  
Fuzzy Model ◽  
Local System ◽  
Linear Matrix ◽  
Fuzzy Modelling ◽  
Ts Fuzzy Model ◽  
Input Noise ◽  
Takagi Sugeno

Abstract This paper examines the problem of designing a robust H∞ fuzzy controller with D-stability constraints for a class of nonlinear dynamic systems which is described by a Takagi-Sugeno (TS) fuzzy model. Fuzzy modelling is a multi-model approach in which simple sub-models are combined to determine the global behavior of the system. Based on a linear matrix inequality (LMI) approach, we develop a robust H∞ fuzzy controller that guarantees (i) the L2-gain of the mapping from the exogenous input noise to the regulated output to be less than some prescribed value, and (ii) the closed-loop poles of each local system to be within a specified stability region. Sufficient conditions for the controller are given in terms of LMIs. Finally, to show the effectiveness of the designed approach, an example is provided to illustrate the use of the proposed methodology.

ADAPTIVE SYNCHRONIZATION OF A NOVEL HYPERCHAOTIC SYSTEM WITH FULLY UNKNOWN PARAMETERS

2013 ◽  
Vol 27 (32) ◽  
pp. 1350197
Author(s):  
XING-YUAN WANG ◽  
SI-HUI JIANG ◽  
CHAO LUO
Keyword(s):  
Lyapunov Stability ◽  
Lyapunov Stability Theory ◽  
Adaptive Controller ◽  
Chaotic Synchronization ◽  
Adaptive Synchronization ◽  
Hyperchaotic System ◽  
Unknown Parameters ◽  
Chen System ◽  
Synchronization Scheme ◽  
Hyperchaotic Systems

In this paper, a chaotic synchronization scheme is proposed to achieve adaptive synchronization between a novel hyperchaotic system and the hyperchaotic Chen system with fully unknown parameters. Based on the Lyapunov stability theory, an adaptive controller and parameter updating law are presented to synchronize the above two hyperchaotic systems. The corresponding theoretical proof is given and numerical simulations are presented to verify the effectiveness of the proposed scheme.

CHAOS AND ROBUST ADAPTIVE SYNCHRONIZATION IN A NONLINEAR EMITTER–RECEIVER SYSTEM

2007 ◽  
Vol 17 (09) ◽  
pp. 3259-3274 ◽  
Author(s):  
F. M. MOUKAM KAKMENI ◽  
SAMUEL BOWONG
Keyword(s):  
Adaptive Observer ◽  
Adaptive Synchronization ◽  
Unknown Parameters ◽  
External Disturbances ◽  
Global Synchronization ◽  
Receiver System ◽  
Lipschitz Constants ◽  
Response Systems ◽  
Robust Adaptive ◽  
Synchronization Scheme

This work studies transitions to chaos and adaptive synchronization of a nonlinear emitter–receiver system in a drive–response framework. Safe bifurcations and explosive bifurcations are observed. A robust adaptive observer-based response system is designed to synchronize the emitter–receiver system with unknown parameters and external disturbances. Lyapunov stability ensures global synchronization between the drive and response systems even if Lipschitz constants on functions matrices and bound on uncertainties are unknown. Computer simulations are provided to illustrate the designed adaptive synchronization scheme.

ADAPTIVE ROBUST SYNCHRONIZATION FOR A CLASS OF DIFFERENT UNCERTAIN CHAOTIC SYSTEMS

2008 ◽  
Vol 22 (23) ◽  
pp. 4069-4082 ◽  
Author(s):  
XINGYUAN WANG ◽  
MINGJUN WANG
Keyword(s):  
Chaotic Systems ◽  
Adaptive Controller ◽  
Adaptive Synchronization ◽  
Unknown Parameters ◽  
Robust Controller ◽  
Synchronization Problem ◽  
Robust Synchronization ◽  
Response Systems ◽  
Uncertain Chaotic Systems ◽  
Predicted Values

This paper addresses the adaptive synchronization problem of a class of different uncertain chaotic systems. A general adaptive robust controller and parameters update rule are designed. It is proved theoretically that the controller and update rule can make the drive-response systems with different structures asymptotically synchronized, and change the unknown parameters to constants when noise exists. When the drive system is certain, the unknown parameters of the response system can be updated to the predicted values. The results of numerical simulations show the effectiveness of the adaptive controller.

Adaptive Fuzzy Synchronization Design and Parameter Identification for Chaotic Systems

2014 ◽  
Vol 644-650 ◽  
pp. 2514-2521
Author(s):  
Juan Meng ◽  
Hai Du ◽  
Xing Yuan Wang
Keyword(s):  
Theoretical Analysis ◽  
Lyapunov Stability ◽  
Chaotic Systems ◽  
Fuzzy Controller ◽  
Fuzzy Model ◽  
Lyapunov Stability Theory ◽  
Unknown Parameters ◽  
Adaptive Fuzzy Controller ◽  
Adaptive Fuzzy ◽  
Takagi Sugeno

In this paper, a new fuzzy model-based adaptive approach for synchronization of chaotic systems with unknown parameters. Theoretical analysis based on Lyapunov stability theory is provided to verify its feasibility. Takagi-Sugeno (T-S) fuzzy model is employed to express the chaotic systems. Based on this model, an adaptive fuzzy controller and the parameters update law are developed. With the proposed scheme, parameters identification and synchronization of identical or nonidentical chaotic systems can be achieved simultaneously. Numerical simulations further demonstrate the effectiveness of the proposed scheme.

ANTICIPATED FUNCTION SYNCHRONIZATION WITH UNKNOWN PARAMETERS OF DISCRETE-TIME CHAOTIC SYSTEMS

2009 ◽  
Vol 20 (04) ◽  
pp. 597-608 ◽  
Author(s):  
YIN LI ◽  
BIAO LI ◽  
YONG CHEN
Keyword(s):  
Chaotic System ◽  
Discrete Time ◽  
Chaos Synchronization ◽  
Chaotic Systems ◽  
Control Law ◽  
Unknown Parameters ◽  
Synchronization Problem ◽  
Synchronization Scheme ◽  
Hyperchaotic Systems ◽  
Function Synchronization

In this paper, firstly, the control problem for the chaos synchronization of discrete-time chaotic (hyperchaotic) systems with unknown parameters are considered. Next, backstepping control law is derived to make the error signals between drive 2D discrete-time chaotic system and response 2D discrete-time chaotic system with two uncertain parameters asymptotically synchronized. Finally, the approach is extended to the synchronization problem for 3D discrete-time chaotic system with two unknown parameters. Numerical simulations are presented to show the effectiveness of the proposed chaos synchronization scheme.

scholarly journals DC MOTOR FUZZY MODEL BASED OPTIMAL CONTROLLER

2021 ◽  
Vol 2021 (4) ◽  
pp. 4879-4885
Author(s):  
DANIELA PERDUKOVA ◽  
◽  
PAVOL FEDOR ◽  
MILAN LACKO ◽  
◽  
...  
Keyword(s):  
Dynamic Systems ◽  
Fuzzy Controller ◽  
Optimality Criterion ◽  
Design Method ◽  
Fuzzy Model ◽  
Dc Motor ◽  
Output Data ◽  
Controlled System ◽  
Model Based ◽  
Measured Input

This paper presents a method for the design of optimal fuzzy controller of a DC motor using a fuzzy model based approach with emphasis on minimal knowledge on the controlled system. In the first part of the paper we describe the method of the black-box fuzzy model design based only on the system´s measured input/output data without the necessity of preliminary knowledge of its internal structure and parameters. This fuzzy model is in the second part used in the design of optimal fuzzy controller based on finding the sequence of input signal values that will transfer the controlled system into the desired state in accordance with the selected optimality criterion. The realized simulation and experimental measurements performed on HIL platform have confirmed the correctness and effectiveness of the proposed design method and also its applicability to others dynamic systems with as little previous knowledge as possible.

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