This paper deals with the stabilization design problem for a class of continuous-time Takagi-Sugeno (T-S) fuzzy model-based control systems. A stabilization design based on fuzzy Lyapunov function and a non-parallel distributed compensation (non-PDC) control law has been proposed. Sufficient stabilization conditions are derived. The conditions for the solvability of the state feedback controlle...

This paper proposes an approach to fuzzy modeling of Anti-lock Braking Systems (ABSs). The local state-space models are derived by the linearization of the nonlinear ABS process model at ten operating points. The Takagi-Sugeno (T-S) fuzzy models are obtained by the modal equivalence principle, where the local state-space models are the rule consequents. The optimization problems are defined in ...

Proportional-integral-derivative (PID) structured controller is the most popular class of industrial control but still could not be appropriately exploited in fuzzy systems. To gain the practicability and tractability of fuzzy systems, this paper develops a parameterized bilinear matrix inequality characterization for the H∞ fuzzy PID control design, which is then relaxed into a bilinear matrix...

A fuzzy fault-tolerant control scheme is proposed for a class of multiple input fuzzy bilinear systems with unmeasurable states. First, a fuzzy detective observer is designed to detect the fault. Based on the developed detective observer, a fuzzy controller is proposed to guarantee the closed-loop system without faults is asymptotically stable. Then, a fuzzy adaptive diagnostic observer is desi...

In recent years, there has been significant interest in the study of stability analysis and con‐ troller synthesis for Takagi-Sugeno(T-S) fuzzy systems, which has been used to approximate certain complex nonlinear systems [1]. Hence it is important to study their stability analysis and controller synthesis. A rich body of literature has appeared on the stability analysis and synthesis problems ...

This paper investigates some properties of Takagi-Sugeno (T-S) fuzzy Hopfield neural networks. First, we prove that there exists a unique solution of the T-S fuzzy Hopfield neural network. Second, we determine a condition for input-to-state stability (ISS) of the T-S fuzzy Hopfield neural network. These results will be useful to analyze dynamic behavior of fuzzy neural networks.

Aneural-learning fuzzy technique is proposed for T–S fuzzy-model identification ofmodel-free physical systems. Further, an algorithm with a defined modelling index is proposed to integrate and to guarantee that the proposed neural-based optimal fuzzy controller can stabilize physical systems; the modelling index is defined to denote the modelling-error evolution, and to ensure that the training...

This paper proposes a novel method for on-line modeling and robust adaptive control via Takagi–Sugeno (T-S) fuzzy models for nonaffine nonlinear systems, with external disturbances. The T-S fuzzy model is established to approximate the nonaffine nonlinear dynamic system in a linearized way. The so-called second type adaptive law is adopted, where not only the consequent part (the weighting fact...

In this paper, a fuzzy model predictive control (FMPC) strategy is proposed to regulate the output variables of a coagulation hemical dosing unit. A multiple-input, multiple-output (MIMO) process model in form of a linearised Takagi–Sugeno (T–S) fuzzy odel is derived. The process model is obtained through subtractive clustering from the plant’s data set. The MIMO model is escribed by a set of c...

This paper discusses conditions on stability and stabilization of continuous T-S fuzzy systems. Stability analysis is derived via non-quadratic Lyapunov function technique and LMIs (Linear Matrix Inequalities) formulation to obtain an efficient solution. The nonquadratic Lyapunov function is built by inference of quadratic Lyapunov function of each local model. We show that stability condition ...