Thesis chaos control

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Show full item record. TS fuzzy approach for modeling, analysis and design of non-smooth dynamical systems. Mehran, Kamyar. There has been growing interest in the past two decades in studying the physical model of dynamical systems that can be described by nonlinear, non-smooth differential equations, i. These systems exhibit more colourful and complex dynamics compared to their smooth counterparts; however, their qualitative analysis and design are not yet fully developed and still open to exploration.

Control of chaos

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Chaos theory is an important aspect of non-linear research, and has infiltrated a number of disciplines and engineering fields. With the increasing scale of power systems, the nonlinear characteristics are more and more obvious, under certain conditions there will even be chaotic behavior, appears as irregular electromechanical oscillations, constituting a threat to the system. So it becomes an urgent need to take effective control measures to curb or eliminate the chaotic oscillations in the non-linear power system. Chaos oscillation in the power system is harmful and should take measures to suppress and eliminate.

Chaos Control method

Do you know any businessperson, artist or politician who became successful just by using a To-Do list, a calendar app or a time management methodology? People don't achieve impressive results simply by being good at task management. It's the ability to set legitimate goals and prioritize that makes the difference. Chaos Control was created to help you manage your goals and desired outcomes in both your business and personal life. Just write them down to make them real.
Chaos theory is a branch of mathematics focusing on the study of chaos — dynamical systems whose apparently random states of disorder and irregularities are actually governed by underlying patterns and deterministic laws that are highly sensitive to initial conditions. Small differences in initial conditions, such as those due to errors in measurements or due to rounding errors in numerical computation, can yield widely diverging outcomes for such dynamical systems, rendering long-term prediction of their behavior impossible in general. The theory was summarized by Edward Lorenz as: [11]. Chaos: When the present determines the future, but the approximate present does not approximately determine the future.
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