Nonlinear and Adaptive Control Design
Nonlinear and Adaptive Control Design
Adaptive backstepping controller design using stochastic small-gain theorem
Automatica (Journal of IFAC)
Fuzzy approximate disturbance decoupling of MIMO nonlinear systems by backstepping approach
Fuzzy Sets and Systems
Automatica (Journal of IFAC)
Automatica (Journal of IFAC)
Automatica (Journal of IFAC)
IEEE Transactions on Neural Networks
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on game theory
Information Sciences: an International Journal
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Paper: The application of fuzzy control systems to industrial processes
Automatica (Journal of IFAC)
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
Stable adaptive fuzzy control of nonlinear systems
IEEE Transactions on Fuzzy Systems
Brief A combined backstepping and small-gain approach to adaptive output feedback control
Automatica (Journal of IFAC)
Expert Systems with Applications: An International Journal
Fuzzy basis functions, universal approximation, and orthogonal least-squares learning
IEEE Transactions on Neural Networks
Adaptive Output-Feedback Fuzzy Tracking Control for a Class of Nonlinear Systems
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
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This paper considers the adaptive fuzzy robust control problem for a class of single-input and single-output (SISO) stochastic nonlinear systems in strict-feedback form. The systems under study possess unstructured uncertainties, unknown dead-zone, uncertain dynamics and unknown gain functions. In the controller design, fuzzy logic systems are adopted to approximate the unknown functions, and the uncertain nonlinear system is therefore transformed into an uncertain parameterized system with unmodeled dynamics. By combining the backstepping technique with the stochastic small-gain approach, a novel adaptive fuzzy robust control scheme is developed. It is shown that the proposed control approach can guarantee that the closed-loop system is input-state-practically stable (ISpS) in probability, and the output of the system converges to a small neighborhood of the origin by appropriately tuning several design parameters. Simulation results are provided to illustrate the effectiveness of the proposed control approach.