UAV control system is a huge and complex system, and to design and test a UAVcontrol system is time-cost and money-cost. This paper considered thesimulation of identification of a nonlinear system dynamics using artificialneural networks approach. This experiment develops a neural network model ofthe plant that we want to control. In the control design stage, experiment usesthe neural network plant model to design (or train) the controller. We useMatlab to train the network and simulate the behavior. This chapter providesthe mathematical overview of MRC technique and neural network architecture tosimulate nonlinear identification of UAV systems. MRC provides a direct andeffective method to control a complex system without an equation-driven model.NN approach provides a good framework to implement MEC by identifyingcomplicated models and training a controller for it.
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