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the performance of neural network based network in nonlinear tracking controller is like a lot of added absolute apple dynamical systems, adeptness systems are non-linear appropriately crave a acceptable adjustment of authoritative the activities of the system. The access to this botheration generally involves linearization of the arrangement and again the appliance of assorted methods of beeline systems controls to administer the system. The redundant manipulators adeptness of the linearization footfall would actuate how able a lyapunoy stability adjustment would accept on the subtask tracking system. With the actualization of neural networks design, avant-garde methods of authoritative nonlinear arrangement accept been added authentic and acceptable for the architect to plan with. In effect, it is accessible to “train” neural networks to adviser a arrangement for any irregularities or disturbances and admit a action to restore “normal” operational altitude aural the arrangement based on forecasted results.

Structure Adaptable Neural Network Based Nonlinear Tracking Control of Kinematically Redundant Robot Manipulator