Chaos simulator as a developing tool and a research environment for applications of chaos engineering

Fuzzy logic, neural networks, and neuro fuzzy technology are now regarded as effective methods for realizing intelligent industrial systems and consumer electronic products. Furthermore, a novel paradigm, 'chaos engineering', is expected to become another key technology for various applications such as nonlinear prediction of time series, nonlinear signal processing, filtering, diagnosis and comfortable home appliances. In this paper, we describe a chaos simulator as a developing tool and a research environment for applications of chaos engineering. This simulator is composed of three modules, such as generation module of chaotic signals by deterministic rules, determination module whether observed time series is chaotic or not, and nonlinear system identification and prediction module by self generating neuro fuzzy model. We also applied this simulator to the development of a kerosene fan heater with chaotic temperature fluctuation control.