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Showing 3 results for Chaos Control

Farhad Pashaei, Seyed Mahdi Abtahi,
Volume 11, Issue 4 (12-2021)

In this paper, firstly chaotic behavior of the lateral dynamics of vehicle is investigated by the use of numerical tools including Lyapunov exponent and bifurcation diagrams. To this end rout to chaos along with period doubling and quasi-periodic responses are demonstrated in terms of bifurcation diagrams. After chaos analysis, a novel controller commensurate with the chaotic characteristics of the system, in conformity with Poincaré map is represented to suppress the chaotic behavior of lateral movement. The Poincaré map of the system is derived by means of a neuro fuzzy network. A robust Fuzzy system on the basis of nonlinear Ott-Grebogi-Yorke (OGY) method forms the control system. Closed-loop results of the system shows effectiveness of the chaos controller in extreme conditions.
Yavar Nourollahi Golouje, Seyyed Mahdi Abtahi, Majid Majidi,
Volume 12, Issue 2 (6-2022)

In this paper, analysis and control of the chaotic vibrations in bounce dynamic of vehicle have been studied according to the comparison of controller based on the nonlinear control and chaos controller on the basis of the chaotic system properties. After modeling the vehicle dynamic, the chaotic behavior of the uncontrolled system was determined using combination of the numerical analysis including bifurcation diagrams and max Lyapunov exponent. The system parameters values were then identified in the quasi-periodic and chaotic behavior system. In order to eliminate the chaotic vibrations, the control signal was first developed using a nonlinear fast-terminal sliding mode control algorithm that its control gains are estimated online by fuzzy logic which was designed for vehicle vertical dynamics. Then the delayed feedback control was designed based on the development of Pyragas algorithm to control the system based on the properties of the chaotic system and generation of a small control signal. Comparison of the feedback system depicts priority of the Fuzzy-Pyragas controller in less energy consumption and better behavior.
Yavar Nourollahi Golouje, Seyyed Mahdi Abtahi, Majid Majidi,
Volume 12, Issue 3 (9-2022)

The chaotic dynamic analysis along with chaos controller of an active suspension in vehicles has been studied in this paper. The unstable periodic orbits of the system are stabilized using the developed delay feedback control algorithm based on the fuzzy sliding mode system. Firstly, the equations of motions in the chaotic half-vehicle model are derived via Newton-Euler rules and simulated by the fourth order Runge-Kutta method. Then, forcing frequency has been used to confirm nonlinear phenomenon such as jump and chaos in the vehicle system. Critical values of the control parameters in the forcing frequency demonstrate the changes of system behavior from the periodic to the irregular chaotic responses. In order to eliminate the chaotic behaviors in the vertical dynamics of vehicle, a novel fuzzy sliding delay feedback control algorithm is developed on the active suspension with chaotic responses. Using fuzzy logic, the controller gain of the sliding delay feedback control is online estimated that is caused to reject the chattering phenomenon in the sliding mode algorithm beside the improvement of the responses. Simulation results of the control system depict a reduction of settling time and energy consumption along with eliminating the overshoots and chaotic vibrations

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