Synchronization Controller Design for Chaotic System with Input Sampled-Data Missing

2014 ◽  
Vol 716-717 ◽  
pp. 1572-1577
Author(s):  
Tao Ren ◽  
Qiang Zhang ◽  
Meng Qian Tang ◽  
Yan Fei Yang
Keyword(s):  
Discrete System ◽  
Chaotic Systems ◽  
Control Method ◽  
Controller Design ◽  
Sampled Data ◽  
Input Method ◽  
Data Control ◽  
Error System ◽  
Data Missing ◽  
Simulation Results

For the chaotic systems with sampled data input, the discontinuous nonlinear system is transformed into a discrete system, and the switched system is proposed considering the control inputs missing. By using the zero input method, a sufficient condition is derived for the exponential stability of the error system. Simulation results illustrate the effectiveness of the proposed sampled-data control method.

Sampled-data vehicular platoon control with communication delay

2017 ◽  
Vol 232 (1) ◽  
pp. 39-49 ◽  
Author(s):  
Jian Gong ◽  
Yuan Zhao ◽  
Zibao Lu
Keyword(s):  
Feedback Linearization ◽  
Control Method ◽  
Controller Design ◽  
Communication Delay ◽  
Communication Strategy ◽  
Control Law ◽  
Sampled Data ◽  
Design Algorithm ◽  
Longitudinal Dynamic ◽  
Data Control

This article investigates sampled-data vehicular platoon control with communication delay. A new sampled-data control method is established, in which the effect of the communication delay is involved. First, a linearized vehicle longitudinal dynamic model is obtained using the exact feedback-linearization technique. Then, under the leader–predecessor following communication strategy, considering communication delay, a platoon control law is proposed based on sampled state information, which allows the weights of state errors to vary along the platoon. Complemented by additional string stability conditions, a useful string-stable platoon controller design algorithm is proposed. Finally, the effectiveness of platoon controller design methodology is demonstrated by numerical examples.

scholarly journals Switched Fuzzy Sampled-Data Control of Chaotic Systems With Input Constraints

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 44402-44410
Author(s):  
Yunjun Chen ◽  
Qiuxia Cao ◽  
Zhenyu Zhu ◽  
Zhangang Wang ◽  
Zhanshan Zhao
Keyword(s):  
Chaotic Systems ◽  
Input Constraints ◽  
Sampled Data ◽  
Data Control ◽  
Sampled Data Control

scholarly journals Finite Time Stability of Finance Systems with or without Market Confidence Using Less Control Input

2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Chao Ma ◽  
Yujuan Tian ◽  
Zhongfeng Qu
Keyword(s):  
Finite Time ◽  
Chaotic Systems ◽  
Control Method ◽  
Control Input ◽  
Three Dimension ◽  
Time Stability ◽  
Finance System ◽  
Finite Time Stability ◽  
Single Controller ◽  
Simulation Results

In this paper, we make an exploration of a technique to control a class of finance chaotic systems. This technique allows one to achieve the finite time stability of the finance system more effectively with less control input energy. First, the finite time stability of three dimension finance system without market confidence is analyzed by using a single controller. Then, two controllers are designed to stabilize the four-dimension finance system with market confidence. Moreover, the finite time stability of the three-dimension and four-dimension finance system with unknown parameter is also studied. Finally, simulation results are presented to show the chaotic behaviour of the finance systems, verify the effectiveness of the proposed control method, and illustrate its advantages compared with other methods.

scholarly journals New Stabilization Results for Semi-Markov Chaotic Systems with Fuzzy Sampled-Data Control

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-15 ◽  
Author(s):  
Tao Wu ◽  
Jinde Cao ◽  
Lianglin Xiong ◽  
Haiyang Zhang
Keyword(s):  
Stability Condition ◽  
Chaotic Systems ◽  
Transition Rates ◽  
Sampled Data ◽  
Markov Jump ◽  
Data Control ◽  
The Stability ◽  
Generally Uncertain Transition Rates ◽  
Delay Dependent ◽  
Sampling Pattern

This paper investigates the problem of stabilization for semi-Markov chaotic systems with fuzzy sampled-data controllers, in which the semi-Markov jump has generally uncertain transition rates. The exponential stability condition is firstly obtained by the following two main techniques: To make full use of the information about the actual sampling pattern, a novel augmented input-delay-dependent Lyapunov–Krasovskii functional (LKF) is firstly introduced. Meanwhile, a new zero-value equation is established to increase the combinations of component vectors of the resulting vector. The corresponding fuzzy sampled-data controllers are designed based on the stability condition. Finally, the validity and merits of the developed theories are shown by two numerical examples.

scholarly journals A non-integer sliding mode controller to stabilize fractional-order nonlinear systems

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Ahmadreza Haghighi ◽  
Roveida Ziaratban
Keyword(s):  
Fractional Order ◽  
Chaotic Systems ◽  
Control Method ◽  
Controller Design ◽  
Nonlinear Dynamical Systems ◽  
Sliding Mode ◽  
Slip Surface ◽  
Direct Method ◽  
Distributed Model ◽  
Sliding Mode Controller

Abstract In this study, we examine the stabilization of fractional-order chaotic nonlinear dynamical systems with model uncertainties and external disturbances. We used the sliding mode controller by a new approach for controlling and stabilization of these systems. In this research, we replaced a continuous function with the sign function in the controller design and the sliding surface to suppress chattering and undesirable vibration effects. The advantages of the proposed control method are rapid convergence to the equilibrium point, the absence of chattering and unwanted oscillations, high resistance to uncertainties, and the possibility of applying this method to most fractional order chaotic systems. We applied the direct method of Lyapunov stability theory and the frequency distributed model to prove the stability of the slip surface and closed loop system. Finally, we simulated this method on two commonly used and practical chaotic systems and presented the results.

Synchronization for hybrid coupled reaction-diffusion neural networks with stochastic disturbances via spatial sampled-data control strategy

2020 ◽  
pp. 095965182093566
Author(s):  
Xiaona Song ◽  
Xingru Li ◽  
Zhaoke Ning ◽  
Mi Wang ◽  
Jingtao Man
Keyword(s):  
Neural Networks ◽  
Controller Design ◽  
Sufficient Conditions ◽  
Coupling Reaction ◽  
Reaction Diffusion ◽  
Sampled Data ◽  
Stochastic Disturbances ◽  
Digital Controllers ◽  
Data Control ◽  
Sampled Data Control

The synchronization of reaction-diffusion neural networks with state and spatial couplings is investigated in this article, and the time-varying delay and stochastic disturbances are considered in the proposed systems. Due to the development and merits of digital controllers, sampled-data control is a natural choice to establish synchronization in continuous-time systems. Here, we suggest a spatial sampled-data controller design, where the sampled-data (in space) measurements of the state are taken in a finite number of fixed sampling points in the spatial domain. It is assumed that the sampling intervals in space are bounded. Based on the Lyapunov stability theory, Young’s and Wirtinger’s inequalities techniques, some sufficient conditions are presented to synchronize the hybrid coupling reaction-diffusion neural networks with stochastic disturbances. Finally, the efficiency of the derived criteria will be demonstrated by resorting to two numerical examples.

Fuzzy resilient control for synchronizing chaotic systems with time-variant delay and external disturbance

2021 ◽  
pp. 2150177
Author(s):  
Weipeng Tai ◽  
Dandan Zuo ◽  
Jing Han ◽  
Jianping Zhou
Keyword(s):  
Chaotic Systems ◽  
Controller Design ◽  
Convex Combination ◽  
External Disturbance ◽  
Synchronization Error ◽  
Disturbance Attenuation ◽  
Resilient Control ◽  
Combination Technique ◽  
Design Scheme ◽  
Error System

This paper focuses on the issue of fuzzy resilient control for synchronizing chaotic systems with time-variant delay and external disturbance. The goal is to design a fuzzy resilient controller with additive gain perturbations to guarantee that not only the drive and response systems are asymptotically synchronized in the absence of external disturbance, but also the synchronization error system has a prescribed disturbance attenuation index under the zero initial condition. By utilizing an appropriate Lyapunov–Krasovskii functional, the Bessel–Legendre inequality, and the reciprocally convex combination technique, a criterion on the stability and [Formula: see text] performance of the synchronization error system is derived. Then, by means of some decoupling methods, a design scheme of the fuzzy resilient controller is developed. Finally, one numerical example is provided to examine the effectiveness of the fuzzy resilient controller design scheme.

scholarly journals State-Feedback Sampled-Data Control Design for Nonlinear Systems via Passive Theory

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Chengming Yang ◽  
Qi Zhou ◽  
H. R. Karimi ◽  
Huanqing Wang
Keyword(s):  
Nonlinear Systems ◽  
Controller Design ◽  
Linear Matrix ◽  
Optimization Approach ◽  
Sampled Data ◽  
Control Approach ◽  
Synthesis Conditions ◽  
Data Control ◽  
Sampled Data Control ◽  
Data Controller

This paper investigates the problem of passive controller design for a class of nonlinear systems under variable sampling. The Takagi-Sugeno (T-S) fuzzy modeling method is utilized to represent the nonlinear systems. Attention is focused on the design of passive controller for the T-S fuzzy systems via sampled-data control approach. Under the concept of very-strict passivity, a novel time-dependent Lyapunov functional is constructed to develop passive analysis criteria and passive controller synthesis conditions. A new sampled-data controller is designed to guarantee that the resulting closed-loop system is very-strictly passive. These conditions are formulated in the form of linear matrix inequalities (LMIs), which can be solved by convex optimization approach. Finally, an application example is given to demonstrate the feasibility and effectiveness of the proposed results.

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