Observer-based robust fuzzy control of nonlinear systems with parametric uncertainties
Fuzzy Sets and Systems - Modeling and control
Effective digital implementation of fuzzy control systems based on approximate discrete-time models
Automatica (Journal of IFAC)
Robust H∞ control for discrete-time fuzzy systems via basis-dependent Lyapunov functions
Information Sciences: an International Journal
IEEE Transactions on Fuzzy Systems
New approaches to relaxed quadratic stability condition of fuzzy control systems
IEEE Transactions on Fuzzy Systems
Robust fuzzy control of nonlinear systems with parametric uncertainties
IEEE Transactions on Fuzzy Systems
A new intelligent digital redesign for T-S fuzzy systems: global approach
IEEE Transactions on Fuzzy Systems
Delay-Dependent Robust Control for T–S Fuzzy Systems With Time Delay
IEEE Transactions on Fuzzy Systems
Digitalizing a Fuzzy Observer-Based Output-Feedback Control: Intelligent Digital Redesign Approach
IEEE Transactions on Fuzzy Systems
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This paper presents a new intelligent digital redesign (IDR) method for uncertain nonlinear systems which are represented by a Takagi-Sugeno (T-S) fuzzy model. The term IDR involves converting an analog controller into an equivalent digital one in the sense of state-matching. The IDR problem can be reduced to finding the digital fuzzy gains minimizing the norm distance between the closed-loop states of the analog and digital control systems. The uncertainties in the plant dynamics are considered in the IDR condition that plays an important role in the performance improvement. Also, the robust stability is well guaranteed in the proposed IDR procedure. Its constructive conditions are expressed as linear matrix inequalities (LMIs). Two numerical examples, the chaotic Lorenz system and the Qi system, are demonstrated to visualize the feasibility of the proposed methodology.