Adaptive neural control of nonlinear time-delay systems with unknown virtual control coefficients

By Shuzhi Sam Ge, Fan Hong, Tong-heng Lee. IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics), 2004

572 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Computer Networks and Communications, Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/a21bed2b1aa102fc9ecabe3dd390801d894ebb11

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Citations in the corpus

Robust adaptive control for a class of uncertain strict‐feedback nonlinear systems (2009, methodology): “In [16, 17], the exponentially decaying terms have been introduced in the controller design to handle the disturbances.”
Adaptive NN Backstepping Output-Feedback Control for Stochastic Nonlinear Strict-Feedback Systems With Time-Varying Delays (2010, methodology): “This modification method has widely been used in the existing work, for example, adaptive control for systems described by the ordinary differential equation [28]–[33], the discrete difference equation [34]–[37], the time-delay functional differential equation [38]–[42], or the Itó stochastic differ”
Adaptive Consensus Control for a Class of Nonlinear Multiagent Time-Delay Systems Using Neural Networks (2014, background): “Solving state time-delay problem is popular in adaptive nonlinear tracking control and rich research results have been reported [28]–[34].”
Prescribed Performance Fault-Tolerant Control of Uncertain Nonlinear Systems With Unknown Control Directions (2017, methodology): “Therefore, the following Nussbaum-type function used within [16], [24] is utilized throughout this note:”
Approximation-based control of nonlinear MIMO time-delay systems (2007, methodology): “(2003), where discontinuous even functions were used, and from (Ge et al., 2004), where piecewise functions were constructed.”
A DSC Approach to Robust Adaptive NN Tracking Control for Strict-Feedback Nonlinear Systems (2008, methodology): “The same RBF NNs (with same nodes, centers, and widths on a regular lattice) as in [14] are employed but with minimal inputs [−1,+1] for W 1 S(x1) and [−1,+1] × [−1.”
Prescribed performance adaptive control of SISO feedback linearizable systems with disturbances (2008, methodology): “Lemma 1: [ 5 ] Let V (t) and ζ(t) be smooth functions defined on [0, tf) with V (t) ≥ 0, ∀t ∈ [0, tf), and N (ζ) be an even smooth Nussbaum-type function.”
Fuzzy-Adaptive Decentralized Output-Feedback Control for Large-Scale Nonlinear Systems With Dynamical Uncertainties (2010, methodology): “However, as stated in [29]–[31], the assumption on the knowledge of the high-frequency-gain sign does not often appear to be realistic in the general case.”