Robust control-based disturbance observer and optimal states feedback for T–S fuzzy systems

2020 ◽  
pp. 146134842098118
Author(s):  
Van-Nam Giap ◽  
Shyh-Chour Huang ◽  
Quang D Nguyen ◽  
Te-Jen Su
Keyword(s):  
Robust Control ◽  
Fuzzy System ◽  
Disturbance Observer ◽  
Stable Region ◽  
Linear Quadratic ◽  
Estimation Errors ◽  
Fuzzy Membership Functions ◽  
Linear Quadratic Regulation ◽  
System States ◽  
Takagi Sugeno

This paper presents a robust control methodology based on a disturbance observer and an optimal states feedback for Takagi–Sugeno fuzzy system. Firstly, the nonlinear systems were solved by applying a sector nonlinearity method to get the inner linear subsystems and outer fuzzy membership functions, which guaranteed the conversion without any loss generality characteristics of the system. Secondly, an exponentially convergent disturbance observer was constructed to the system with an assumption that the system states are temporarily bounded. Thirdly, a states observer was built by poles placement of linear quadratic regulation optimization, which was used to place the system states error poles located on the stable region. Finally, simulation examples were given to figure out that the proposed controller is effective to control the Takagi–Sugeno fuzzy system. The obtained results are disturbance mostly rejected, state estimation errors are quite small, and the output signal precisely tracked input signal.

Rule Reduction and Robust Control of Generalized Takagi-Sugeno Fuzzy Systems

2000 ◽  
Vol 4 (5) ◽  
pp. 373-379 ◽  
Author(s):  
Tadanari Taniguchi ◽  
◽  
Kazuo Tanaka ◽  
Keyword(s):  
Robust Control ◽  
Model Reduction ◽  
Fuzzy System ◽  
Fuzzy Systems ◽  
Controller Design ◽  
Main Idea ◽  
Linear Matrix ◽  
Robust Controller ◽  
Reduction Error ◽  
Takagi Sugeno

This paper presents model reduction and robust control using a generalized form of Takagi-Sugeno fuzzy systems. We first define a generalized form of TakagiSugeno fuzzy systems. The generalized form has a decomposed structure for each element of <I>Ai</I> and <I>Bi</I> matrices in consequent parts. The key feature of this structure is that it is suitable for reducing the number of rules. Conditions to reduce the number of rules are represented in terms of linear matrix inequality (LMIs). The main idea is to find a structure of if-then rules of the reduced model that agrees well with dynamics of the original model. Furthermore, we estimate the lower bound of the norm of model uncertainty of the Takagi-Sugeno fuzzy system that can cover the reduction error. Finally, we present an example of model reduction and robust control for a nonlinear system. In this example, we achieve a robust controller design to compensate for the uncertainly of the Takagi-Sugeno fuzzy system.

GENERATING CHAOS VIA FEEDBACK CONTROL FROM A STABLE TS FUZZY SYSTEM THROUGH A SINUSOIDAL NONLINEARITY

2002 ◽  
Vol 12 (10) ◽  
pp. 2283-2291 ◽  
Author(s):  
ZHONG LI ◽  
JIN BAE PARK ◽  
GUANRONG CHEN ◽  
YOUNG HOON JOO ◽  
YOON HO CHOI
Keyword(s):  
Feedback Control ◽  
Fuzzy System ◽  
Controller Design ◽  
State Feedback Control ◽  
Small Magnitude ◽  
Controlled System ◽  
Bounded State ◽  
System States ◽  
Takagi Sugeno ◽  
Uniformly Bounded

An approach is proposed for making chaotic a given stable Takagi–Sugeno (TS) fuzzy system using state feedback control of arbitrarily small magnitude. The feedback controller chosen among several candidates is a simple sinusoidal function of the system states, which can lead to uniformly bounded state vectors of the controlled system with positive Lyapunov exponents, and satisfy the chaotic mechanisms of stretching and folding, thereby yielding chaotic dynamics. This approach is mathematically proven for rigorous generation of chaos from a stable TS fuzzy system, where the chaos is in the sense of Li and Yorke. A numerical example is included to visualize the theoretical analysis and the controller design.

scholarly journals Real-Time Energy Management of Parallel Hybrid Electric Vehicles Using Linear Quadratic Regulation

Energies ◽  
2020 ◽  
Vol 13 (21) ◽  
pp. 5538
Author(s):  
Bảo-Huy Nguyễn ◽  
João Pedro F. Trovão ◽  
Ronan German ◽  
Alain Bouscayrol
Keyword(s):  
Real Time ◽  
Energy Management ◽  
Electric Vehicles ◽  
Hybrid Electric Vehicles ◽  
Engine Fuel ◽  
Linear Quadratic ◽  
Loop Control ◽  
Parallel Hybrid ◽  
Linear Quadratic Regulation ◽  
Hybrid Electric

Optimization-based methods are of interest for developing energy management strategies due to their high performance for hybrid electric vehicles. However, these methods are often complicated and may require strong computational efforts, which can prevent them from real-world applications. This paper proposes a novel real-time optimization-based torque distribution strategy for a parallel hybrid truck. The strategy aims to minimize the engine fuel consumption while ensuring battery charge-sustaining by using linear quadratic regulation in a closed-loop control scheme. Furthermore, by reformulating the problem, the obtained strategy does not require the information of the engine efficiency map like the previous works in literature. The obtained strategy is simple, straightforward, and therefore easy to be implemented in real-time platforms. The proposed method is evaluated via simulation by comparison to dynamic programming as a benchmark. Furthermore, the real-time ability of the proposed strategy is experimentally validated by using power hardware-in-the-loop simulation.

scholarly journals Sliding Mode Robust Control of a Wire-Driven Parallel Robot Based on HJI Theory and a Disturbance Observer

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 215235-215245
Author(s):  
Yuqi Wang ◽  
Qi Lin ◽  
Jiacai Huang ◽  
Lei Zhou ◽  
Jinjiang Cao ◽  
...  
Keyword(s):  
Robust Control ◽  
Disturbance Observer ◽  
Sliding Mode ◽  
Parallel Robot

Integral terminal sliding-mode robust vibration control of large space intelligent truss structures using a disturbance observer

2021 ◽  
pp. 095441002110290
Author(s):  
Dalong Tian ◽  
Jianguo Guo
Keyword(s):  
Robust Control ◽  
Forced Vibration ◽  
Disturbance Observer ◽  
Sliding Mode ◽  
External Disturbance ◽  
Truss Structures ◽  
Model Parameters ◽  
Large Space ◽  
Terminal Sliding Mode ◽  
Piezoelectric Stack Actuator

This study aims to develop an advanced integral terminal sliding-mode robust control method using a disturbance observer (DO) to suppress the forced vibration of a large space intelligent truss structure (LSITS). First, the dynamics of the electromechanical coupling of the piezoelectric stack actuator and the LSITS, based on finite element and Lagrangian methods, are established. Subsequently, to constrict the vibration of the structure, a novel integral terminal sliding-mode control (ITSMC) law for the DO is used to estimate the parameter perturbation of the LSITS based on a continuous external disturbance. Simulation results show that, under a forced vibration and compared with the ITSMC system without a DO, the displacement amplitude of the ITSMC system with the DO is effectively reduced. In the case where the model parameters of the LSITS deviate by ±50%, and an unknown continuous external disturbance exists, the control system with the DO can adequately attenuate the structural vibration and realize robust control. Concurrently, the voltage of the employed piezoelectric stack actuator is reduced, and voltage jitter is alleviated.

Robust Tracking Control for Takagi–Sugeno Fuzzy Systems With Unmeasurable Premise Variables: Application to Tank System

2014 ◽  
Vol 136 (4) ◽  
Author(s):  
H. Ghorbel ◽  
A. El Hajjaji ◽  
M. Souissi ◽  
M. Chaabane
Keyword(s):  
Tracking Control ◽  
Fuzzy Systems ◽  
Design Procedure ◽  
Control Design ◽  
Linear Matrix ◽  
Robust Tracking Control ◽  
Fuzzy Observer ◽  
Tank System ◽  
System States ◽  
Takagi Sugeno

In this paper, a robust fuzzy observer-based tracking controller for continuous-time nonlinear systems presented by Takagi–Sugeno (TS) models with unmeasurable premise variables, is synthesized. Using the H∞ norm and Lyapunov approach, the control design for TS fuzzy systems with both unmeasurable premises and system states is developed to guarantee tracking performance of closed loop systems. Sufficient relaxed conditions for synthesis of the fuzzy observer and the fuzzy control are driven in terms of linear matrix inequalities (LMIs) constraints. The proposed method allows simplifying the design procedure and gives the observer and controller gains in only one step. Numerical simulation on a two tank system is provided to illustrate the tracking control design procedure and to confirm the efficiency of the proposed method.

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