Fuzzy Control of Inverted Robot Arm with Perturbed Time-Delay Affine Takagi-Sugeno Fuzzy Model

2007 ◽  
Author(s):  
Wen-Jer Chang ◽  
Wei-Han Huang ◽  
Wei Chang
Keyword(s):  
Time Delay ◽  
Fuzzy Control ◽  
Fuzzy Model ◽  
Robot Arm ◽  
Takagi Sugeno

SYNCHRONIZATION OF TIME-DELAYED T–S FUZZY CHAOTIC SYSTEMS VIA SCALAR OUTPUT VARIABLE

2005 ◽  
Vol 15 (08) ◽  
pp. 2593-2601 ◽  
Author(s):  
JAE-HUN KIM ◽  
HYUNSEOK SHIN ◽  
EUNTAI KIM ◽  
MIGNON PARK
Keyword(s):  
Time Delay ◽  
Fuzzy Model ◽  
Order System ◽  
Linear Matrix ◽  
Output Variable ◽  
First Order ◽  
Scalar Output ◽  
The Stability ◽  
Takagi Sugeno ◽  
System With Time Delay

It has been known that very complex chaotic behaviors can be observed in a simple first-order system with time-delay. This paper presents a fuzzy model-based approach for synchronization of time-delayed chaotic system via a scalar output variable. Takagi–Sugeno (T–S) fuzzy model can represent a general class of nonlinear system and we employ it for fuzzy modeling of the chaotic drive and response system with time-delay. Since only a scalar output variable is available for synchronization, a fuzzy observer based on T–S fuzzy model is designed and applied to chaotic synchronization. We analyze the stability of the overall fuzzy synchronization system by applying Lyapunov–Krasovskii theory and derive stability conditions by solving linear matrix inequalities (LMI's) problem. A numerical example is given to demonstrate the validity of the proposed synchronization approach.

Finite time takagi-sugeno fuzzy control for hydro-turbine governing system

2016 ◽  
Vol 24 (5) ◽  
pp. 1001-1010 ◽  
Author(s):  
Bin Wang ◽  
Jianyi Xue ◽  
Fengjiao Wu ◽  
Delan Zhu
Keyword(s):  
Fuzzy Control ◽  
Finite Time ◽  
Control Method ◽  
Fuzzy Model ◽  
Schur Complement ◽  
Stability Control ◽  
Linear Matrix ◽  
Hydro Turbine ◽  
Governing System ◽  
Takagi Sugeno

In this study, a robust finite time Takagi-Sugeno fuzzy control method for hydro-turbine governing system (HTGS) is investigated. Firstly, the mathematical model of HTGS is introduced, and on the basis of Takagi-Sugeno (T-S) fuzzy rules, the T-S fuzzy model of HTGS is presented. Secondly, based on finite time stability theory, a novel finite time Takagi-Sugeno fuzzy control method is designed for the stability control of HTGS. Thirdly, the relatively loose sufficient stability condition is acquired, which could be transformed into a group of linear matrix inequalities (LMIs) via Schur complement as well as the strict mathematical derivation is given. Furthermore, the control method could resist random disturbances, which shows the good robustness. Simulation results indicate the designed finite time T-S fuzzy control scheme works well compared with the conventional method. The approach proposed in this paper is easy to implement and also provides reference for relevant hydropower systems.

Optimal parallel-distributed-compensation controller design for a class of time-varying Takagi–Sugeno fuzzy model–based time-delay systems by using the orthogonal function approach–assisted genetic algorithm

2020 ◽  
pp. 107754632093690
Author(s):  
Fu-I Chou ◽  
Ming-Ren Hsu ◽  
Wen-Hsien Ho
Keyword(s):  
Genetic Algorithm ◽  
Time Delay ◽  
Controller Design ◽  
Fuzzy Model ◽  
Time Varying ◽  
Orthogonal Function ◽  
Model Based ◽  
Delay Control ◽  
Takagi Sugeno ◽  
Delay Control Systems

This study proposes a method of designing quadratic optimal fuzzy parallel-distributed-compensation controllers for a class of time-varying Takagi–Sugeno fuzzy model–based time-delay control systems used to solve the finite-horizon optimal control problem. The proposed method fuses the orthogonal function approach and the improved hybrid Taguchi-genetic algorithm. The Taguchi-genetic algorithm only requires algebraic computation to perform the algorithm used to solve time-varying Takagi–Sugeno fuzzy model–based time-delay feedback dynamic equations. The fuzzy parallel-distributed-compensation controller design problem is simplified by using the Taguchi-genetic algorithm to transform the static parameter optimization problem into an algebraic equation. The static optimization problem can then be solved easily by using the improved hybrid Taguchi-genetic algorithm to find the quadratic optimal parallel-distributed-compensation controllers of the time-varying Takagi–Sugeno fuzzy model–based time-delay control systems. The applicability of the proposed integrative method is demonstrated in a real-world design problem.

State Feedback Stabilization in Nonlinear Time-Delay Systems

2002 ◽  
Vol 6 (3) ◽  
pp. 109-114
Author(s):  
Tsuyoshi Hori ◽  
◽  
Kazuo Tanaka
Keyword(s):  
Time Delay ◽  
Controller Design ◽  
Fuzzy Model ◽  
Main Idea ◽  
Feedback Stabilization ◽  
Delay Systems ◽  
Control Synthesis ◽  
Linear Matrix ◽  
Time Delay Systems ◽  
Takagi Sugeno

In this paper, a class of nonlinear time-delay systems based on the Takagi-Sugeno (T-S) fuzzy model is defined. We investigate the delay-independent stability of this model. A model-based fuzzy stabilization design utilizing the concept of parallel distributed compensation (PDC) is employed. The main idea of the controller design is to derive each control rule to compensate each rule of a fuzzy system. Moreover, the problem of H∞ of this class of nonlinear time-delay systems is considered. The associated control synthesis problems are formulated as linear matrix inequality (LMI) problems.

scholarly journals Analysis, Filtering, and Control for Takagi-Sugeno Fuzzy Models in Networked Systems

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Sunjie Zhang ◽  
Zidong Wang ◽  
Jun Hu ◽  
Jinling Liang ◽  
Fuad E. Alsaadi
Keyword(s):  
Fuzzy Control ◽  
Fuzzy Systems ◽  
Nonlinear Function ◽  
Fuzzy Model ◽  
Dynamic Structure ◽  
Future Research ◽  
Compact Set ◽  
Great Success ◽  
Randomly Occurring Uncertainties ◽  
Takagi Sugeno

The fuzzy logic theory has been proven to be effective in dealing with various nonlinear systems and has a great success in industry applications. Among different kinds of models for fuzzy systems, the so-called Takagi-Sugeno (T-S) fuzzy model has been quite popular due to its convenient and simple dynamic structure as well as its capability of approximating any smooth nonlinear function to any specified accuracy within any compact set. In terms of such a model, the performance analysis and the design of controllers and filters play important roles in the research of fuzzy systems. In this paper, we aim to survey some recent advances on the T-S fuzzy control and filtering problems with various network-induced phenomena. The network-induced phenomena under consideration mainly include communication delays, packet dropouts, signal quantization, and randomly occurring uncertainties (ROUs). With such network-induced phenomena, the developments on T-S fuzzy control and filtering issues are reviewed in detail. In addition, some latest results on this topic are highlighted. In the end, conclusions are drawn and some possible future research directions are pointed out.

Nonlinear control design using Takagi-Sugeno fuzzy applied to under-actuated visual servo system

2020 ◽  
Vol 42 (15) ◽  
pp. 2969-2983
Author(s):  
Vimala Kumari Jonnalagadda ◽  
Vinodh Kumar Elumalai ◽  
Harvir Singh ◽  
Amit Prasad
Keyword(s):  
Fuzzy Control ◽  
Moving Objects ◽  
Direct Method ◽  
Fuzzy Model ◽  
Control Design ◽  
Linear Matrix ◽  
Nonlinear Stabilization ◽  
Ts Fuzzy Model ◽  
Takagi Sugeno ◽  
Plate System

This paper presents the Takagi-Sugeno (TS) fuzzy control design for nonlinear stabilization and tracking control of a ball on plate system. To deal with the plant nonlinearity and the fuzzy convergence issue, we formulate the parallel distributed compensator (PDC) TS fuzzy model to characterize the global behaviour of the nonlinear system and synthesize a feasible control framework using a velocity compensation scheme. The nonlinear dynamics of the ball on plate system is obtained using the Euler-Lagrangian energy based approach. To identify the moving objects in the video stream, a background subtraction algorithm using thresholding technique is formulated. Moreover, the stability analysis of the TS fuzzy control is reduced to linear matrix inequality (LMI) problem and solved using the Lyapunov direct method. The potential benefits of the proposed control structure for real time test cases are experimentally assessed using hardware in loop (HIL) testing on a ball on plate system. Experimental results substantiate that the TS fuzzy scheme can significantly improve not only the tracking performance but also the robustness of the closed loop system.

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