Fuzzy model based integral action sliding mode control

2003 ◽  
Vol 7 (4) ◽  
pp. 244-251 ◽  
Author(s):  
M. J. Knight ◽  
R. Sutton ◽  
R. S. Burns
Keyword(s):  
Sliding Mode Control ◽  
Sliding Mode ◽  
Fuzzy Model ◽  
Model Based ◽  
Mode Control ◽  
Integral Action

Design of robust fuzzy-model-based controller with sliding mode control for SISO nonlinear systems

2002 ◽  
Vol 125 (1) ◽  
pp. 1-22 ◽  
Author(s):  
Wook Chang ◽  
Jin Bae Park ◽  
Young Hoon Joo ◽  
Guanrong Chen
Keyword(s):  
Nonlinear Systems ◽  
Sliding Mode Control ◽  
Sliding Mode ◽  
Fuzzy Model ◽  
Model Based ◽  
Mode Control

scholarly journals Fuzzy-Model-Based Sliding Mode Control of Nonlinear Descriptor Systems

2019 ◽  
Vol 49 (9) ◽  
pp. 3409-3419 ◽  
Author(s):  
Yueying Wang ◽  
Hamid Reza Karimi ◽  
Hao Shen ◽  
Zhijun Fang ◽  
Mingxin Liu
Keyword(s):  
Sliding Mode Control ◽  
Sliding Mode ◽  
Fuzzy Model ◽  
Descriptor Systems ◽  
Model Based ◽  
Mode Control

scholarly journals The Approximation of the Nonlinear Singular System with Impulses and Sliding Mode Control via a Singular Polynomial Fuzzy Model Approach

Symmetry ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1409
Author(s):  
Jiawen Li ◽  
Yi Zhang ◽  
Zhenghong Jin
Keyword(s):  
Sliding Mode Control ◽  
Sliding Mode ◽  
Singular System ◽  
Fuzzy Model ◽  
Switching Function ◽  
Covering Theorem ◽  
Function Type ◽  
Numerical Examples ◽  
Mode Control ◽  
Nonlinear Singular System

In this paper, the Singular-Polynomial-Fuzzy-Model (SPFM) approach problem and impulse elimination are investigated based on sliding mode control for a class of nonlinear singular system (NSS) with impulses. Considering two numerical examples, the SPFM of the nonlinear singular system is calculated based on the compound function type and simple function type. According to the solvability and the steps of two numerical examples, the method of solving the SPFM form of the nonlinear singular system with (and without) impulse are extended to the more general case. By using the Heine–Borel finite covering theorem, it is proven that a class of nonlinear singular systems with bounded impulse-free item (BIFI) properties and separable impulse item (SII) properties can be approximated by SPFM with arbitrary accuracy. The linear switching function and sliding mode control law are designed to be applied to the impulse elimination of SPFM. Compared with some published works, a human posture inverted pendulum model example and Example 3.2 demonstrate that the approximation error is small enough and that both algorithms are effective. Example 3.3 is to illustrate that sliding mode control can effectively eliminate impulses of SPFM.

Nonlinear observer based sliding mode control and oxygen fraction estimation for diesel engine

2017 ◽  
Vol 40 (7) ◽  
pp. 2227-2239 ◽  
Author(s):  
Haoping Wang ◽  
Qiankun Qu ◽  
Yang Tian
Keyword(s):  
Diesel Engine ◽  
Sliding Mode Control ◽  
Oxygen Concentration ◽  
Control Method ◽  
Sliding Mode ◽  
Observer Design ◽  
Nonlinear Observer ◽  
Linear Matrix ◽  
Model Based ◽  
Mode Control

In this paper, a nonlinear observer based sliding mode control (NOSMC) approach for air-path and a model-based observer for oxygen concentration in the diesel engine equipped with a variable geometry turbocharger and exhaust gas recirculation is introduced. We propose a less conservative observer design technique for Lipschitz nonlinear systems using Ricatti equations. The observer gains are obtained by solving the linear matrix inequality (LMI). Then a robust nonlinear control method, sliding mode control is applied for the states of intake and exhaust manifold pressure and compressor mass flow rate for the sake of the minimization of emissions. The proposed NOSMC controller is applied on a mean value model of turbocharged diesel engine. Besides this, a model-based observer is developed to estimate the oxygen concentration in the intake and exhaust manifolds owing to its significance in reducing emissions of diesel engines. The validation and efficiency of the proposed method are demonstrated by AMESim and Matlab/Simulink co-simulation results.

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