Robust chaos suppression of uncertain unified chaotic systems based on chattering-free sliding mode control

Lin, Chih‐Hsueh; Ho, Chia-Wei; Hu, Guo-Hsin; Sreeramaneni, Baswanth; Yan, Jun Juh

doi:10.1177/00202940221090272

Cited by 6 publications

(2 citation statements)

References 24 publications

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“…Since the meteorologist Lorenz proposed chaos theory, researchers have discovered chaos in many engineering fields. 1 As the core part of switching power supply, DC-DC converter is widely used in instruments, electric vehicles, green energy and other systems. [2][3][4] In practical operation, DC-DC converter will produce complex and abundant nonlinear physical phenomena (such as bifurcation, chaos, etc.…”

Section: Introductionmentioning

confidence: 99%

Model-free adaptive chaos control for the boost converter

Li,

Jiang,

Wei

2023

Measurement and Control

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In order to solve the dynamic analysis and chaotic motion control problems of the current-mode-controlled Boost converter system, a state equation model in the continuous current mode is established. The evolutionary path of the periodic motion of the system through the doubling bifurcation to the chaotic motion is analyzed by the bifurcation diagram, Poincaré sections and phase portraits. Then, according to the fundamental principle of the resonant parametric perturbation (RPP) method, a controller is designed based on the model-free adaptive control (MFAC) method to output the perturbation amplitude, and the disturbance quantity is calculated according to the perturbation amplitude. By adding a small amplitude disturbance to the controllable parameter of the controlled system, the chaotic motion of the system is guided to expected periodic orbit. The advantage of this method is that no precise mathematical model (PMM) of the system is required. At the same time, the design of the controller is simple and easy to implement.

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Section: Introductionmentioning

confidence: 99%

Model-free adaptive chaos control for the boost converter

Li,

Jiang,

Wei

2023

Measurement and Control

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“…Some aspects of chaotic systems have been studied, and some control techniques for various applications have been proposed. The studies in the field of control can be categorized in two classes: classic and FLS-based controllers [9,10].…”

Section: Introductionmentioning

confidence: 99%

A New Type-3 Fuzzy Logic Approach for Chaotic Systems: Robust Learning Algorithm

et al. 2022

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The chaotic systems have extensive applications in various branches of engineering problems such as financial problems, image processing, secure communications, and medical problems, among many others. In most applications, a synchronization needs to be made with another favorite chaotic system, or output trajectories track the desired signal. The dynamics of these systems are complicated, they are very sensitive to the initial conditions, and they exhibit a stochastic unpredictable behavior. In this study, a new robust type-3 fuzzy logic control (T3-FLC) is designed that can be applied for a large case of chaotic systems under faulty actuators and unknown perturbed dynamics. The dynamic uncertainties are estimated by the online learned type-3 fuzzy logic systems (T3-FLSs). The rules of T3-FLS are optimized by the Lyapunov theorem. The actuator nonlinearities are identified by a new method. The effects of approximation error (AE), dynamic perturbations and unknown time-varying control gains are tackled by the designed adaptive compensator. The designed compensator is constructed by online estimation of the upper bound of AE. By several simulations and comparison with the new FLS-based controllers, the better performance of the designed T3-FLC is shown. In addition, the performance of the designed controller is examined in a secure communication system.

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Neural network-based integral sliding mode control of arbitrary nonlinear systems with unknown bounded disturbances

Nathasarma,

Roy

2023

Int. J. Dynam. Control

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Robust chaos suppression of uncertain unified chaotic systems based on chattering-free sliding mode control

Cited by 6 publications

References 24 publications

Model-free adaptive chaos control for the boost converter

Model-free adaptive chaos control for the boost converter

A New Type-3 Fuzzy Logic Approach for Chaotic Systems: Robust Learning Algorithm

Neural network-based integral sliding mode control of arbitrary nonlinear systems with unknown bounded disturbances

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