Technical results for the study of robustness of Lagrange stability
Systems & Control Letters
Adaptive robust control of SISO nonlinear systems in a semi-strict feedback form
Automatica (Journal of IFAC)
Fuzzy adaptive backstepping robust control for SISO nonlinear system with dynamic uncertainties
Information Sciences: an International Journal
Adaptive fuzzy control for strict-feedback canonical nonlinear systems with H∞ tracking performance
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Adaptive neural control of nonlinear time-delay systems with unknown virtual control coefficients
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
IEEE Transactions on Fuzzy Systems
Adaptive Fuzzy Output Tracking Control of MIMO Nonlinear Uncertain Systems
IEEE Transactions on Fuzzy Systems
Adaptive Control of a Class of Nonlinear Pure-Feedback Systems Using Fuzzy Backstepping Approach
IEEE Transactions on Fuzzy Systems
Design of Robust Adaptive Controllers for Nonlinear Systems with Dynamic Uncertainties
Automatica (Journal of IFAC)
Robust adaptive neural control for a class of perturbed strict feedback nonlinear systems
IEEE Transactions on Neural Networks
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In this paper, an adaptive fuzzy robust output feedback control approach is proposed for a class of SISO nonlinear strict-feedback systems with unknown sign of high-frequency gain and the unmeasured states. The nonlinear systems addressed in this paper are assumed to possess the unmodeled dynamics, dynamical disturbances and unknown nonlinear functions, where the unknown nonlinear functions are not linearly parameterized, and no prior knowledge of their bounds is available. In the recursive designing, fuzzy logic systems are used to approximate the unknown nonlinear functions, K-filters are designed to estimate the unmeasured states, and a dynamical signal and Nussbaum gain functions are introduced to handle the unmodeled dynamics and the unknown sign of the high-frequency gain, respectively. Based on Lyapunov function method, a stable adaptive fuzzy output feedback control scheme is developed. It is mathematically proved that the proposed adaptive fuzzy control approach can guarantee that all the signals of the closed-loop system are uniformly ultimately bounded, the output converges to a small neighborhood of the origin. The effectiveness of the proposed approach is illustrated by the simulation examples.