Synchronization of FitzHugh–Nagumo systems in EES via H∞ variable universe adaptive fuzzy control

In this paper, H_∞ variable universe adaptive fuzzy control law is derived and applied to synchronize two FitzHugh—Nagumo neurons. Firstly, the different dynamical behavior of the nonlinear cable model based on the FitzHugh–Nagumo model responding to the various external electrical simulations (EES) is studied. Next, using the result of the analysis, a robust adaptive variable universe fuzzy control scheme is designed to synchronize two neurons. The computer simulations is provided for verify the efficiency of the designed synchronization scheme.     

Synchronization of Ghostburster neuron in external electrical stimulation via H∞ variable universe fuzzy adaptive control

In this paper, H_∞ variable universe fuzzy adaptive control law is derived and applied to synchronize two unidirectional coupled Ghostbursters neurons under external electrical stimulation. Firstly, the dynamical behavior of the nonlinear Ghostburster model responding to various external electrical stimulations is studied. Then, using the results of the analysis, a robust adaptive variable universe fuzzy control scheme is designed to synchronize two unidirectional coupled neurons. Numerical simulations demonstrate the validity and feasibility of the proposed method.     

Adaptive fuzzy sliding-mode control for multi-input multi-output chaotic systems

This paper describes an adaptive fuzzy sliding-mode control algorithm for controlling unknown or uncertain, multi-input multi-output (MIMO), possibly chaotic, dynamical systems. The control approach encompasses a fuzzy system and a robust controller. The fuzzy system is designed to mimic an ideal sliding-mode controller, and the robust controller compensates the difference between the fuzzy controller and the ideal one. The parameters of the fuzzy system, as well as the uncertainty bound of the robust controller, are tuned adaptively. The adaptive laws are derived in the Lyapunov sense to guarantee the asymptotic stability and tracking of the controlled system. The effectiveness of the proposed method is shown by applying it to some well-known chaotic systems.     

Chaos synchronization and parameter identification for loudspeaker systems

The identical two-degrees-of-freedom loudspeaker systems are discussed for synchronization of chaos in this paper. Two methods are used to synchronize two identical chaotic systems with different initial condition: the adaptive control and the Gerschgorin's theorem. Finally we research the parameter identification for two identical two-degrees-of-freedom loudspeaker systems by adaptive control and random optimization method.     

Unidirectional synchronization of Hodgkin–Huxley neurons exposed to ELF electric field

In this paper, a hybrid control strategy, H_∞ variable universe adaptive fuzzy control, is derived and applied to synchronize two Hodgkin–Huxley (HH) neurons exposed to external electric field. Firstly, the modified model of HH neuron exposed to extremely low frequency (ELF) external electric field is established and its periodic and chaotic dynamics in response to sinusoidal electric field stimulation are described. And then the statement of the problem for unidirectional synchronization of two HH neurons is given. Finally H_∞ variable universe adaptive fuzzy control is designed to synchronize the HH systems and the simulation results demonstrate the effectiveness of the proposed control method.     

Synchronization of mechanical horizontal platform systems in finite time

The horizontal platform system (HPS) is a mechanical device that exhibits rich and chaotic dynamics. In this paper, the problem of finite-time synchronization of two non-autonomous chaotic HPSs is investigated. It is assumed that both drive and response systems are disturbed by model uncertainties, external disturbances and fully unknown parameters. Appropriate update laws are proposed to undertake the unknown parameters. Using the update laws and finite-time control theory, a robust adaptive controller is derived to synchronize the two uncertain HPSs in a given finite time. Subsequently, the effects of input nonlinearities are taken into account and a robust adaptive controller is introduced to synchronize the two uncertain HPSs within a finite time. The finite-time stability and convergence of the proposed schemes are analytically proved. Two illustrative examples are presented to show the robustness and applicability of the proposed adaptive finite-time control techniques.     

多输入多输出非线性最小相位系统的自适应模糊控制

针对多输入多输出非线性最小相位系统,把自适应模糊控制和自适应模糊辨识结合起来,提出了一种自适应模糊控制方案.设计辨识器用来辨识系统的未知部分;然后由跟踪误差和辨识误差给出了参数调节规律,两种误差同时调节参数改善了系统性能.模糊逻辑系统用来估计未知函数.控制方案保证了系统的稳定性,实现了有界跟踪.仿真结果表明了该方案的可行性.     

Adaptive control and synchronization of a new modified hyperchaotic Lü system with uncertain parameters

This paper addresses problems of control and synchronization for a new modified hyperchaotic Lü system with uncertain parameters. This new modified uncertain hyperchaotic Lü system is stabilized to its unique unstable equilibrium by using adaptive control. Furthermore, an adaptive control law and a parameter estimation update law are derived to synchronize two identical modified hyperchaotic Lü systems with uncertain parameters. Numerical examples are proposed to demonstrate and verify the theoretical analysis.     

Synchronization and secure communication of chaotic systems via robust adaptive high-gain fuzzy observer

This paper proposes an alternative robust adaptive high-gain fuzzy observer design scheme and its application to synchronization and secure communication of chaotic systems. It is assumed that their states are immeasurable and their parameters are unknown. The structure of the proposed observer is represented by Takagi–Sugeno fuzzy model and has the integrator of the estimation error. It improves the performance of high-gain observer and makes the proposed observer robust against noisy measurements, uncertainties and parameter perturbations as well. Using Lyapunov stability theory, an adaptive law is derived to estimate the unknown parameters and the stability of the proposed observer is analyzed. Some simulation result of synchronization and secure communication of chaotic systems is given to present the validity of theoretical derivations and the performance of the proposed observer as an application.     

A chattering-free robust adaptive sliding mode controller for synchronization of two different chaotic systems with unknown uncertainties and external disturbances

In this paper, a robust adaptive sliding mode controller (RASMC) is introduced to synchronize two different chaotic systems in the presence of unknown bounded uncertainties and external disturbances. The structure of the master and slave chaotic systems has no restrictive assumption. Appropriate adaptation laws are derived to tackle the uncertainties and external disturbances. Based on the adaptation laws and Lyapunov stability theory, an adaptive sliding control law is designed to ensure the occurrence of the sliding motion even when both master and slave systems are perturbed with unknown uncertainties and external disturbances. Since the conventional sliding mode controllers contain the sign function, the undesirable chattering is occurred. We propose a new simple adaptive scheme to eliminate the chattering. Finally, numerical simulations are presented to verify the usefulness and applicability of the proposed control strategy.     

组合型自适应模糊控制器的设计与分析

充分利用被控对象与控制行为的知识,为一类非线性系统设计一个组合型自适应模糊控制器。它的主要特点是设计一个自适应补偿器来减小建模误差和参数估计误差对系统性能的影响。在不要求最优逼近误差平方可积和上界已知的条件下,证明闭环系统全局渐近稳定,所有信号有界且跟踪误差收敛到零。     

Switched modified function projective synchronization of hyperchaotic Qi system with uncertain parameters

This work is involved with switched modified function projective synchronization of two identical Qi hyperchaotic systems using adaptive control method. Switched synchronization of chaotic systems in which a state variable of the drive system synchronize with a different state variable of the response system is a promising type of synchronization as it provides greater security in secure communication. Modified function projective synchronization with the unpredictability of scaling functions can enhance security. Recently formulated hyperchaotic Qi system in the hyperchaotic mode has an extremely broad frequency bandwidth of high magnitudes, verifying its unusual random nature and indicating its great potential for some relevant engineering applications such as secure communications. By Lyapunove stability theory, the adaptive control law and the parameter update law are derived to make the state of two chaotic systems modified function projective synchronized. Synchronization under the effect of noise is also considered. Numerical simulations are presented to demonstrate the effectiveness of the proposed adaptive controllers.     

Adaptive fuzzy tracking control for the chaotic permanent magnet synchronous motor drive system via backstepping

An adaptive fuzzy control method is developed to suppress chaos in the permanent magnet synchronous motor drive system via backstepping technology. Fuzzy logic systems are used to approximate unknown nonlinearities and an adaptive backstepping technique is employed to construct controllers. Compared with the conventional backstepping, the designed fuzzy controllers’ structure is very simple. The simulation results indicate that the proposed control scheme can suppress the chaos of PMSM drive systems and track the reference signal successfully even under the parameter uncertainties.     

Regularized Adaptation of Fuzzy Inference Systems. Modelling the Opinion of a Medical Expert about Physical Fitness: An Application

This study presents a new approach to adaptation of Sugeno type fuzzy inference systems using regularization, since regularization improves the robustness of standard parameter estimation algorithms leading to stable fuzzy approximation. The proposed method can be used for modelling, identification and control of physical processes. A recursive method for on-line identification of fuzzy parameters employing Tikhonov regularization is suggested. The power of approach was shown by applying it to the modelling, identification, and adaptive control problems of dynamic processes. The proposed approach was used for modelling of human-decisions (experience) with a fuzzy inference system and for the fuzzy approximation of physical fitness with real world medical data.     

一类高阶非完整系统的鲁棒适应模糊控制

针对一类带有强漂移项的高阶非完整系统,基于后推设计方法,input-state-scaling变换技巧和模糊系统的逼近能力提出了一种新的自适应控制方案.该方案保证闭环系统的所有信号最终一致有界,且系统的状态收敛到零的一个小邻域内.     

Fuzzy control of a class of multivariable nonlinear systems subject to parameter uncertainties: model reference approach

This paper presents the fuzzy control of a class of multivariable nonlinear systems subject to parameter uncertainties. The nonlinear plant tackled in this paper is an nth-order nonlinear system with n inputs. If the input matrix B inside the fuzzy plant model is invertible, a fuzzy controller can be designed such that the states of the closed-loop system will follow those of a user-defined stable reference model despite the presence of parameter uncertainties. A numerical example will be given to show the design procedures and the merits of the proposed fuzzy controller.     

Modeling and control of nonlinear systems using novel fuzzy wavelet networks: The output adaptive control approach

This paper proposes an observer based self-structuring robust adaptive fuzzy wave-net (FWN) controller for a class of nonlinear uncertain multi-input multi-output systems. The control signal is comprised of two parts. The first part arises from an adaptive fuzzy wave-net based controller that approximates the system structural uncertainties. The second part comes from a robust H_∞ based controller that is used to attenuate the effect of function approximation error and disturbance. Moreover, a new self structuring algorithm is proposed to determine the location of basis functions. Simulation results are provided for a two DOF robot to show the effectiveness of the proposed method.     

Fast synchronization of non-identical chaotic modulation-based secure systems using a modified sliding mode controller

In this paper, a secure communication scheme based on chaotic modulation is proposed using a reversible process and a robust controller with efficient cost and complexity to synchronize two different chaotic systems. In the controller design, a sliding mode control with an adaptive rule is used for non-linear inputs. The adaptive rule is applied to ensure the synchronization when uncertainties, non-modeled dynamics or external distortions are at work. The message signal is recovered at the receiver using a recursive process at the end. The effectiveness of the proposed algorithm is confirmed via the simulation results for the synchronization of the transmitted signal modulated by Chen chaotic system at the transmitter and Genesio chaotic system at the receiver, and those for the information recovery process.     

Weak synchronization of chaotic neural networks with parameter mismatch via periodically intermittent control

This paper deals with the synchronization of two coupled identical chaotic systems with parameter mismatch via using periodically intermittent control. In general, parameter mismatches are considered to have a detrimental effect on the synchronization quality between coupled identical systems: in the case of small parameter mismatches the synchronization error does not decay to zero or even a nonzero mean. Larger values of parameter mismatches can even result in the loss of synchronization. via intermittent control with periodically intervals, we can obtain the weak synchronization. Some sufficient conditions for the stabilization and weak synchronization of a large class of coupled identical chaotic systems will be derived by using Lyapunov stability theory. The analytical results are confirmed by numerical simulations.     

Adaptive fuzzy control for a class of chaotic systems with nonaffine inputs

A robust adaptive fuzzy control scheme is presented for a class of chaotic systems with nonaffine inputs, modeling uncertainties and external disturbances by using backstepping approach. Fuzzy logic systems (FLS) are employed to approximate the unknown parts of the virtual control and practical controls. The main characteristics of the scheme are that the number of the online adaptive parameters is no more than two times of the order of chaotic system and the tracking errors are guaranteed to be uniformly asymptotically stable with the aid of additional adaptive compensation terms. Lorenz system, Chen system, Lü system and Liu system are presented to illustrate the feasibility and effectiveness of the proposed control technique.