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In this paper, a new multi-layer neural network (MNN) based system identification scheme in discrete-time is proposed for a general class of nonlinear discrete-time systems with guaranteed asymptotic convergence of the identification error. Then, a MNN based direct adaptive MNN controller design is introduced for a different class of nonlinear discrete-time systems. The unique aspect of the proposed...
The problem of designing robust tracking controls for a large class of robots actuated by brushed direct current motors is addressed. This class of electrically driven robots can be perturbed by plant uncertainties, unmodelled time-varying perturbations and external disturbances. Adaptive neural network (or fuzzy) systems are employed to approximate the behaviours of uncertain dynamics, and the variable...
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