A Genesio-Tesi chaotic control using an adaptive-neural observer based RISE controller

Measurement and observation of chaotic system states are major challenge in the control engineering. Due to lack of availability of the states, the control purpose fails to realize required performance. In this paper a new observer based structure is proposed to control the chaos. The recently developed RISE feedback controller is combined with an adaptive-Neural observer to control the Genesio-Tesi chaotic system. Unlike to other conventional structures of neural network the applied observer is trained on-line. Performance of the proposed controller is investigated through simulation.