A course in fuzzy systems and control
A course in fuzzy systems and control
Fuzzy model identification: selected approaches
Fuzzy model identification: selected approaches
Design of fuzzy sliding-mode control systems
Fuzzy Sets and Systems
Adaptive fuzzy sliding mode control with GA-based reaching laws
Fuzzy Sets and Systems
Adaptive fuzzy sliding mode controller for linear systems with mismatched time-varying uncertainties
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Adaptive and robust controller design for uncertain nonlinear systems via fuzzy modeling approach
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Fuzzy adaptive sliding-mode control for MIMO nonlinear systems
IEEE Transactions on Fuzzy Systems
Automatica (Journal of IFAC)
An adaptive fuzzy sliding mode controller for remotely operated underwater vehicles
Robotics and Autonomous Systems
CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
IEEE Transactions on Fuzzy Systems
Type-2 fuzzy sliding mode control without reaching phase for nonlinear system
Engineering Applications of Artificial Intelligence
Robust H∞ control for a class of discrete time fuzzy systems via delta operator approach
Information Sciences: an International Journal
Hi-index | 22.15 |
An adaptive sliding mode control (ASMC) technique based on T-S fuzzy system models is proposed in this paper for a class of perturbed nonlinear MIMO dynamic systems in order to solve tracking problems. A T-S fuzzy model is firstly formed by utilizing fuzzy theorem to amalgamate a set of linearized dynamic equations. The adaptive sliding mode controller is then designed based on this fuzzy model with perturbations. The proposed control scheme can drive the dynamics of controlled system into a designated sliding surface in finite time, and guarantee the property of asymptotical stability. It is also shown that the information of upper bound of modeling errors as well as perturbations, except the information of upper bound of input uncertainty, is not required when using the proposed controller.