Chaotic synchronization using PID control combined with population based incremental learning algorithm

Coelho, Leandro dos Santos; Grebogi, Rafael Bartnik

doi:10.1016/j.eswa.2010.01.022

Cited by 28 publications

(10 citation statements)

References 24 publications

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“…EAs have been also frequently used in the task of synchronization of chaos [13–15]. In [16], an EA for optimizing local control of chaos based on a Lyapunov approach is presented.…”

Section: Introductionmentioning

confidence: 99%

Chaos Enhanced Differential Evolution in the Task of Evolutionary Control of Selected Set of Discrete Chaotic Systems

Šenkeřík

Zelinka

Pluháček

et al. 2014

The Scientific World Journal

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Evolutionary technique differential evolution (DE) is used for the evolutionary tuning of controller parameters for the stabilization of set of different chaotic systems. The novelty of the approach is that the selected controlled discrete dissipative chaotic system is used also as the chaotic pseudorandom number generator to drive the mutation and crossover process in the DE. The idea was to utilize the hidden chaotic dynamics in pseudorandom sequences given by chaotic map to help differential evolution algorithm search for the best controller settings for the very same chaotic system. The optimizations were performed for three different chaotic systems, two types of case studies and developed cost functions.

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“…EAs have been also frequently used in the task of synchronization of chaos [13–15]. In [16], an EA for optimizing local control of chaos based on a Lyapunov approach is presented.…”

Section: Introductionmentioning

confidence: 99%

Chaos Enhanced Differential Evolution in the Task of Evolutionary Control of Selected Set of Discrete Chaotic Systems

Šenkeřík

Zelinka

Pluháček

et al. 2014

The Scientific World Journal

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“…The state equations of the multi-wing chaotic Chen attractor whose states are to be controlled are given by (8). The suggested parameters for 4 N = are given in (9) for which the chaotic Chen system exhibits multi-wing attractors in phase portraits.…”

Section: Chaotic Multi-wing Chen Systemmentioning

confidence: 99%

Simulation studies on the design of optimum PID controllers to suppress chaotic oscillations in a family of Lorenz-like multi-wing attractors

Das

Acharya

Pan

2014

Mathematics and Computers in Simulation

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Abstract:Multi-wing chaotic attractors are highly complex nonlinear dynamical systems with higher number of index-2 equilibrium points. Due to the presence of several equilibrium points, randomness and hence the complexity of the state time series for these multi-wing chaotic systems is much higher than that of the conventional double-wing chaotic attractors. A real-coded Genetic Algorithm (GA) based global optimization framework has been adopted in this paper as a common template for designing optimum Proportional-Integral-Derivative (PID) controllers in order to control the state trajectories of four different multi-wing chaotic systems among the Lorenz family viz. Lu system, Chen system, Rucklidge (or Shimizu Morioka) system and Sprott-1 system. Robustness of the control scheme for different initial conditions of the multi-wing chaotic systems has also been shown.

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“…Coelho [20] has proposed a tuning method for determining the parameters of PID control for an automatic regulator voltage (AVR) system using a chaotic optimization approach based on Lozi map. Coelho and Grebogi [21] have presented the synchronization of two identical discrete chaotic systems subject to the different initial conditions by designing a Proportional-Integral-Derivative (PID) controller. Menhas et al [22] have presented a new variant of binary particle swarm optimization (PSO) algorithm; called probability based binary PSO (PBPSO), to tune the parameters of a coordinated controller.…”

Section: Introductionmentioning

confidence: 99%

Design and performance analysis of PID controller for an automatic voltage regulator system using simplified particle swarm optimization

Panda

Sahu

Mohanty

2012

Journal of the Franklin Institute

205

119

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Chaotic synchronization using PID control combined with population based incremental learning algorithm

Cited by 28 publications

References 24 publications

Chaos Enhanced Differential Evolution in the Task of Evolutionary Control of Selected Set of Discrete Chaotic Systems

Chaos Enhanced Differential Evolution in the Task of Evolutionary Control of Selected Set of Discrete Chaotic Systems

Simulation studies on the design of optimum PID controllers to suppress chaotic oscillations in a family of Lorenz-like multi-wing attractors

Design and performance analysis of PID controller for an automatic voltage regulator system using simplified particle swarm optimization

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