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This paper presents an efficient hybrid feedback feedforward (HFF) adaptive approximation-based control (AAC) strategy for a class of uncertain Euler–Lagrange systems. The control structure includes a proportional–derivative (PD) control term in the feedback loop and a radial-basis-function (RBF) neural network (NN) in the feedforward loop, which mimics the human motor learning control mechanism....
This paper presents a simplified adaptive backstepping neural network control (ABNNC) strategy for a general class of uncertain strict-feedback nonlinear systems. In the backstepping design, all unknown functions at intermediate steps are passed down such that only a single neural network is needed to approximate a lumped uncertainty at the last step. The closed-loop system achieves practical asymptotic...
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