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An adaptive approach that augments existing decentralized linear controllers is considered. By employing a neural network as a centralized element, the approach greatly broadens the class of system for which linear decentralized controllers can be designed. The stability proof naturally follows from the viewpoint that a set of decentralized controllers are a special class of multi-input multi-output...
For a class of single-input single-output non-affine non-minimum phase nonlinear systems, a neural control synthesis method based on backstepping combined with inverting design is considered. The method reduces the number of steps in designing a backstepping controller compared to previous approaches by seeking a state that stabilizes the unstable internal dynamics. The method does not need a fixed-point...
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