Fuzzy Control Systems Design and Analysis: A Linear Matrix Inequality Approach

By Kazuo Tanaka, Hong Wang. 2008

3,901 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/331ace8e416d66e4187b4158456515a7add3f0b7

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Citations in the corpus

A Novel Approach to Filter Design for T–S Fuzzy Discrete-Time Systems With Time-Varying Delay (2012, methodology): “By using the same procedure as in [30], the nonlinear term θ2(k) can be exactly represented as θ2(k) = h1(θ(k))(−M)θ(k) + h2(θ(k))Mθ(k)”
Influence of the Tensor Product Model Representation of qLPV Models on the Feasibility of Linear Matrix Inequality Based Stability Analysis (2018, methodology): “The LMI based control design techniques require a convex TP model representation of the model S(p(t)) [3,4,20,22].”
A new fuzzy Lyapunov function approach for a Takagi-Sugeno fuzzy control system design (2006, methodology): “8 shows the stabilizable region of the conventional Lyapunov function approaches [8,13,16,17,19].”
Adaptive Sliding Mode Control for Interval Type-2 Fuzzy Systems (2016, background): “Example 2: Consider the following Rossler’s equation [63] with input term:”
Perspectives of fuzzy systems and control (2005, background): “This idea, for TS fuzzy systems called parallel distributed compensation [53], has proven very fruitful .”
Stability Analysis of Interval Type-2 Fuzzy-Model-Based Control Systems (2008, methodology): “The stability region indicated by crosses for [4] is shown in Fig.”
Polytopic Decomposition of Linear Parameter-Varying Models by Tensor-Product Model Transformation (2006, methodology): “The derivation and the proof of the theorem is fully detailed in [80].”
Robust Adaptive Sliding-Mode Control for Fuzzy Systems With Mismatched Uncertainties (2010, methodology): “Here, we approximate the system by the following two-rule fuzzy model [38].”
A Sum-of-Squares Approach to Modeling and Control of Nonlinear Dynamical Systems With Polynomial Fuzzy Systems (2009, methodology): “5 shows the feasible area of the LMI design conditions (36)–(38) consisting of the T–S fuzzy model (57) and the corresponding PDC fuzzy controller [21].”
Adaptive Sliding-Mode Control for Nonlinear Active Suspension Vehicle Systems Using T–S Fuzzy Approach (2013, methodology): “For the uncertain active suspension systems, it is feasible to apply the Takagi–Sugeno (T–S) fuzzy approach to handle the uncertainties since the T–S fuzzy model is very effective in representing complex nonlinear systems [16], [17].”
State feedback control of switched linear systems: an LMI approach (2006, background): “for Takagi–Sugeno fuzzy systems [26] could be applied to switched linear systems.”
A survey on industrial applications of fuzzy control (2011, neutral): “This idea is known as parallel distributed compensation [18].”
A New Approach to Stability Analysis and Stabilization of Discrete-Time T-S Fuzzy Time-Varying Delay Systems (2011, neutral): “By using the same procedure as in [20], the nonlinear term θ(2) can be exactly represented as θ(2)(k) = h1 (θ(k)) (−m)θ(k) + h2 (θ(k)) mθ(k)”
A Descriptor System Approach to Fuzzy Control System Design via Fuzzy Lyapunov Functions (2007, methodology): “S) fuzzy model [1] have received a great deal of attention over the last decade (e.g., see [2]–[15]).”