Control of chaos and/or turbulence is an important topic in plasma physics. For fusion plasmas, the suppression of anomalous transport is critical issue to attain the self-ignition conditions. To establish controlling method of turbulence, we start from chaos control as a first step. The delayed feedback controlling method proposed by Pyragas is well known, which is a linear controlling method[1]. Using the method, the Rossler model is investigated. A chaos is successfully controlled to be a limit cycle state. Instantaneous Lyapunov exponents are calculated for the system and the suppression of chaos is confirmed. Power spectrum is also calculated and the period of limit cycle is evaluated. It is found that the controlling chaos critically depends on the gain K. Therefore we limit the absolute value of perturbation, i.e., K|y(t)-y(t-τ)| less than unity. The delay time τ is chosen so that the perturbation has a local minimum which corresponds to the period of limit cycle. For the period - one or two cycles, we successfully control them for an arbitrary initial condition, however, for the period three cycles, successful control depends on the choice of the initial condition. The neural network is also applied to the model. To evolve the weight of neural network, we use so called `SANE`(Symbiotic Adaptive Neuro-Evolution)[2]. The comparison studies between linear and nonlinear controlling methods of chaos will be reported in detail in this conference.

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