Neural Network Control of Robot Manipulators and Nonlinear Systems
Neural Network Control of Robot Manipulators and Nonlinear Systems
Adaptive Neural Network Control of Robotic Manipulators
Adaptive Neural Network Control of Robotic Manipulators
Stable Adaptive Neural Network Control
Stable Adaptive Neural Network Control
Stable Adaptive Control and Estimation for Nonlinear Systems: Neural and Fuzzy Approximation Techniques
Adaptive Approximation Based Control: Unifying Neural, Fuzzy and Traditional Adaptive Approximation Approaches (Adaptive and Learning Systems for Signal Processing, Communications and Control Series)
Sampled-data adaptive NN tracking control of uncertain nonlinear systems
IEEE Transactions on Neural Networks
Identification of nonlinear dynamic systems using functional linkartificial neural networks
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Neural Networks
High-order neural network structures for identification of dynamical systems
IEEE Transactions on Neural Networks
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The asymptotic tracking control problem of a class of single-input single-output (SISO) uncertain nonlinear systems is addressed in this paper. A single-hidden layer neural network is used as a controller with a novel online weight training algorithm. The proposed NN weight update law mimics standard second order sliding mode control (2-SMC) approaches to ensure semi-global asymptotic convergence of the tracking error to the origin with continuous control effort. A simulation study verifies the effectiveness of the NN controller with 2-SMC-based online training.