scholarly journals Sliding Mode Control of the Fractional-Order Unified Chaotic System

2013 ◽  
Vol 2013 ◽  
pp. 1-13 ◽  
Author(s):  
Jian Yuan ◽  
Bao Shi ◽  
Xiaoyun Zeng ◽  
Wenqiang Ji ◽  
Tetie Pan
Keyword(s):  
Sliding Mode Control ◽  
Fractional Order ◽  
Chaotic Systems ◽  
Sliding Mode ◽  
Adaptive Sliding Mode Control ◽  
External Disturbances ◽  
Mode Control ◽  
Unified Chaotic System ◽  
Unified Chaotic Systems ◽  
Systematic Uncertainties

This paper deals with robust synchronization of the fractional-order unified chaotic systems. Firstly, control design for synchronization of nominal systems is proposed via fractional sliding mode technique. Then, systematic uncertainties and external disturbances are considered in the fractional-order unified chaotic systems, and adaptive sliding mode control is designed for the synchronization issue. Finally, numerical simulations are carried out to verify the effectiveness of the two proposed control techniques.

Stabilization of a Class of Fractional-Order Chaotic Systems via Direct Adaptive Fuzzy Optimal Sliding Mode Control

2018 ◽  
pp. 289-304
Author(s):  
Bachir Bourouba
Keyword(s):  
Sliding Mode Control ◽  
Fractional Order ◽  
Chaotic Systems ◽  
Sliding Mode ◽  
Optimization Technique ◽  
External Disturbances ◽  
Control Approach ◽  
Adaptive Fuzzy ◽  
Mode Control ◽  
Fuzzy Control Strategy

In this chapter a new direct adaptive fuzzy optimal sliding mode control approach is proposed for the stabilization of fractional chaotic systems with different initial conditions of the state under the presence of uncertainties and external disturbances. Using Lyapunov analysis, the direct adaptive fuzzy optimal sliding mode control approach illustrates asymptotic convergence of error to zero as well as good robustness against external disturbances and uncertainties. The authors present a method for optimum tuning of sliding mode control system parameter using particle swarm optimization (PSO) algorithm. PSO is a robust stochastic optimization technique based on the movement and intelligence of swarm, applying the concept of social interaction to problem solving. Simulation examples for the control of nonlinear fractional-order systems are given to illustrate the effectiveness of the proposed fractional adaptive fuzzy control strategy.

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