Abstract
This paper introduces a decoupled adaptive neuro-fuzzy (DANF) sliding mode control system for the chaos control problem in a system without precise system model information. It has on-line learning ability to deal with the parametric uncertainty and disturbance by adjusting the control parameters and no constrained conditions and prior knowledge of the controlled plant is required in the design process. Also, a decoupled adaptive sliding mode controller is developed to control the chaotic Lorenz system for comparison. Finally, the effectiveness of the proposed decoupled adaptive sliding mode and DANF sliding mode controllers are demonstrated by some simulated results.
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