We propose a new type of neural adaptive control via dynamic neural networks. For a class of unknown nonlinear systems, a\r\nneural identifier-based feedback linearization controller is first used. Dead-zone and projection techniques are applied to assure\r\nthe stability of neural identification. Then four types of compensator are addressed. The stability of closed-loop system is also\r\nproven.
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