Tesfay G. Meressi
Learning Control, Iterative, Fuzzy, Robotics
A nonlinear mathematical model of a robotic fish and an iterative learning controller were used to generate feed-forward inputs to a system. A fuzzy logic trajectory tracking controller is then added to bring the deviation between the outputs of the ideal (approximate) system and the assumed actual system within specified bounds. Numerical simulations were carried out to show the effectiveness of the learning plus fuzzy controller in achieving the desired trajectory.
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