Design of a sliding mode fuzzy observer for uncertain Takagi-Sugeno fuzzy model: application to automatic steering of vehicles

2007 ◽  
Vol 5 (3/4) ◽  
pp. 288 ◽  
Author(s):  
A. Akhenak ◽  
M. Chadli ◽  
J. Ragot ◽  
D. Maquin
Keyword(s):  
Sliding Mode ◽  
Fuzzy Model ◽  
Model Application ◽  
Fuzzy Observer ◽  
Automatic Steering ◽  
Takagi Sugeno

Fuzzy observer–based disturbance rejection control for nonlinear fractional-order systems with time-varying delay

2021 ◽  
pp. 107754632110069
Author(s):  
Parvin Mahmoudabadi ◽  
Mahsan Tavakoli-Kakhki
Keyword(s):  
Fractional Order ◽  
Disturbance Rejection ◽  
State Feedback ◽  
Sufficient Conditions ◽  
Fuzzy Model ◽  
Linear Matrix ◽  
Delayed Systems ◽  
Fuzzy Observer ◽  
Time Varying Delay ◽  
Takagi Sugeno

In this article, a Takagi–Sugeno fuzzy model is applied to deal with the problem of observer-based control design for nonlinear time-delayed systems with fractional-order [Formula: see text]. By applying the Lyapunov–Krasovskii method, a fuzzy observer–based controller is established to stabilize the time-delayed fractional-order Takagi–Sugeno fuzzy model. Also, the problem of disturbance rejection for the addressed systems is studied via the state-feedback method in the form of a parallel distributed compensation approach. Furthermore, sufficient conditions for the existence of state-feedback gains and observer gains are achieved in the terms of linear matrix inequalities. Finally, two numerical examples are simulated for the validation of the presented methods.

scholarly journals Development of Fuzzy Observer Gain Design Algorithm for Ship Path Estimation Based on AIS Data

Processes ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 33
Author(s):  
Chin-Lin Pen ◽  
Wen-Jer Chang ◽  
Yann-Horng Lin
Keyword(s):  
Dynamic Systems ◽  
Design Method ◽  
Fuzzy Model ◽  
Observer Design ◽  
Nonlinear Observer ◽  
Automatic Identification ◽  
Identification System ◽  
Design Algorithm ◽  
Fuzzy Observer ◽  
Takagi Sugeno

This paper develops a Takagi-Sugeno fuzzy observer gain design algorithm to estimate ship motion based on Automatic Identification System (AIS) data. Nowadays, AIS data is widely applied in the maritime field. To solve the problem of safety, it is necessary to accurately estimate the trajectory of ships. Firstly, a nonlinear ship dynamic system is considered to represent the dynamic behaviors of ships. In the literature, nonlinear observer design methods have been studied to estimate the ship path based on AIS data. However, the nonlinear observer design method is challenging to create directly since some dynamic ship systems are more complex. This paper represents nonlinear ship dynamic systems by the Takagi-Sugeno fuzzy model. Based on the Takagi-Sugeno fuzzy model, a fuzzy observer design method is developed to solve the problem of estimating using AIS data. Moreover, the observer gains of the fuzzy observer can be adjusted systemically by a novel algorithm. Via the proposed algorithm, a more suitable or better observer can be obtained to achieve the objectives of estimation. Corresponding to different AIS data, the better results can also be obtained individually. Finally, the simulation results are presented to show the effectiveness and applicability of the proposed fuzzy observer design method. Some comparisons with the previous nonlinear observer design method are also given in the simulations.

Backstepping quasi-continuous high-order sliding mode control for a Takagi–Sugeno fuzzy system with an application for a two-link robot control

2013 ◽  
Vol 228 (9) ◽  
pp. 1488-1500 ◽  
Author(s):  
Mien Van ◽  
Hee-Jun Kang ◽  
Kyoo-Sik Shin
Keyword(s):  
Sliding Mode Control ◽  
Fuzzy System ◽  
Motion Tracking ◽  
Sliding Mode ◽  
Fuzzy Model ◽  
Second Order ◽  
High Order ◽  
Mode Control ◽  
Takagi Sugeno ◽  
Second Order Sliding Mode

A new control scheme is proposed for motion tracking of a Takagi–Sugeno fuzzy system using the backstepping quasi-continuous high-order sliding mode (HOSM) control technique. First, a Takagi–Sugeno fuzzy model is used to represent the original second-order nonlinear system; most of the parameters for this model can be computed offline. Next, a conventional backstepping sliding mode control (BSMC) is designed to stabilize and guarantee the exact motion tracking for the Takagi–Sugeno fuzzy system. However, use of the conventional sliding mode control generates significant chattering. Therefore, a quasi-continuous second-order sliding mode (QC2S) control is employed to reduce chattering and obtain higher tracking precision, resulting in a backstepping quasi-continuous second-order sliding mode (BQC2S) control law. Combining the Takagi–Sugeno fuzzy model with the BQC2S controller results in a controller scheme that preserves the advantages of both techniques, such as the low online computational burden of the Takagi–Sugeno fuzzy model, and the low chattering, robustness, and fast transient response of the BQC2S controller. Finally, the proposed controller is used to control a two-link robot manipulator and is compared with the existing approaches. Simulation results are presented to demonstrate the effectiveness of the proposed methodology.

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