Title :
TSK Observers for Discrete Type-1 and Type-2 Fuzzy Systems
Author :
Fadali, Mohammed Sami ; Jafarzadeh, Saeed
Author_Institution :
Dept. of Electr. & Biomed. Eng., Univ. of Nevada Reno, Reno, NV, USA
Abstract :
This paper proposes a new observer design methodology for type-1 and type-2 Takagi-Sugeno-Kang fuzzy systems. The design methodology does not require a common Lyapunov function and is, therefore, applicable to systems with nondetectable consequents. Our observers include fuzzy observers as well as constant gain observers. The observers are exponentially stable, and the designer can specify the rate of exponential convergence. The observer designs can be tested using linear matrix inequalities. The observers can be combined with a fuzzy controller for observer state feedback. The observer design methodology is demonstrated using the TORA system, and the observer state feedback is applied to the control of the inverted pendulum. The results show that the observer design provides good estimates of the state and can be used in a control system design even if the system has nondetectable consequents. Comparison to results from the literature shows that the new design can provide stable observer state feedback, where other observer designs fail.
Keywords :
asymptotic stability; control system synthesis; convergence; discrete systems; fuzzy control; fuzzy systems; linear matrix inequalities; nonlinear control systems; observers; pendulums; state feedback; TORA system; TSK observer design methodology; Takagi-Sugeno-Kang fuzzy system; constant gain observer; control system design; discrete type-1 fuzzy system; discrete type-2 fuzzy system; exponential convergence rate; exponential stability; fuzzy controller; fuzzy observer; inverted pendulum control; linear matrix inequalities; observer state feedback; state estimation; Convergence; Design methodology; Fuzzy systems; Observers; Stability analysis; State feedback; Vectors; State observer; Takagi–Sugeno–Kang (TSK) systems; type-2 fuzzy systems;
Journal_Title :
Fuzzy Systems, IEEE Transactions on
DOI :
10.1109/TFUZZ.2013.2251886