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Composite learning control with modular backstepping and high-order tuners
Adaptive control of strict-feedback nonlinear systems with mismatched uncertainties remains challenging because high-order derivatives of parameter estimates can degrade transient tracking, while parameter convergence typically requires the stringent condition of persistent excitation (PE). This pap
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