Fuzzy Passivity Control of Flexible Joint Robot

2013 ◽  
Vol 834-836 ◽  
pp. 1229-1233
Author(s):  
Bin Zhang
Keyword(s):  
Control Method ◽  
Fuzzy Controller ◽  
Fuzzy Model ◽  
Model Error ◽  
Stability Control ◽  
Linear Matrix ◽  
Matrix Inequalities ◽  
Flexible Joint ◽  
Single Link ◽  
The Stability

This paper researches a fuzzy control method for passive flexible joint robot. Stability control method applying T-S fuzzy model is employed for single-link flexible joint robot. T-S fuzzy model is used to approximate the flexible joint robot firstly, and then fuzzy controller is developed based on the principle of parallel distributed compensation. The fuzzy controller is also applied to the passive properties of model error. The stability conditions are proposed by Lyapunov function and linear matrix inequalities are also applied to solve the controller parameters. Simulation results show that the proposed method of application value.

Fuzzy Passivity Non-Fragile Control of Flexible Joint Robot

2013 ◽  
Vol 448-453 ◽  
pp. 3571-3575
Author(s):  
Bin Zhang
Keyword(s):  
Robot Control ◽  
Simulation Experiment ◽  
Fuzzy Controller ◽  
Fuzzy Model ◽  
Linear Matrix ◽  
Matrix Inequality ◽  
Flexible Joint ◽  
Control Approach ◽  
Compensation Principle ◽  
The Stability

The paper proposes a fuzzy passivity non-fragile control approach for flexible joint robot. The T-S fuzzy model is applied to approximate the flexible joint robot at first, and then the fuzzy controller is developed based on parallel distributed compensation principle. The passivity non-fragile performance of controller is also employed to limit the influence of model error. The conditions for the stability of the flexible joint robot control system are proposed by using Lyapunov function, and linear matrix inequality is applied to resolve the controller parameter. The simulation experiment results show the effectiveness of the proposed method.

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.

H∞ Control of Flexible Joint Robot via T-S Fuzzy Model

2011 ◽  
Vol 128-129 ◽  
pp. 894-897
Author(s):  
Feng Wang ◽  
Xiao Ping Liu
Keyword(s):  
Robot Control ◽  
Fuzzy Controller ◽  
Fuzzy Model ◽  
Stability Conditions ◽  
Modeling Error ◽  
Flexible Joint ◽  
Control Approach ◽  
Compensation Principle ◽  
Simulation Results ◽  
The Stability

In this paper, a H∞ control approach based on T-S fuzzy model for flexible joint robot is proposed. First, the Takagi and Sugeno (T-S) fuzzy model is applied to approximate the flexible joint robot. Then, a fuzzy controller is developed based on parallel distributed compensation principle (PDC), and H∞ performance is employed to restrain the influence of modeling error caused by variety of stiffness. The stability conditions for the flexible joint robot control system are proposed by Lyapunov function. Finally, the simulation results are given to show the effectiveness of the proposed method.

Reliable Robust H∞ Fuzzy Control for Uncertain Nonlinear Systems With Markovian Jumping Actuator Faults

2006 ◽  
Vol 129 (3) ◽  
pp. 252-261 ◽  
Author(s):  
Huai-Ning Wu
Keyword(s):  
Fuzzy Control ◽  
Fuzzy Controller ◽  
Fuzzy Model ◽  
Disturbance Attenuation ◽  
Linear Matrix ◽  
Actuator Faults ◽  
Markovian Jumping ◽  
Stochastically Stable ◽  
The Stability ◽  
Time Systems

This paper is concerned with the design of reliable robust H∞ fuzzy control for uncertain nonlinear continuous-time systems with Markovian jumping actuator faults. The Takagi and Sugeno fuzzy model is employed to represent an uncertain nonlinear system with Markovian jumping actuator faults. First, based on the parallel distributed compensation (PDC) scheme, a sufficient condition such that the closed-loop fuzzy system is robustly stochastically stable and satisfies a prescribed level of H∞-disturbance attenuation is derived. In the derivation process, a stochastic Lyapunov function is used to test the stability and H∞ performance of the system. Then, a new improved linear matrix inequality (LMI) formulation is applied to this condition to alleviate the interrelation between the stochastic Lyapunov matrix and system matrices containing controller variables, which results in a tractable LMI-based condition for the existence of reliable and robust H∞ fuzzy controllers. A suboptimal fuzzy controller is proposed to minimize the level of disturbance attenuation subject to the LMI constraints. Finally, a simulation example is given to illustrate the effectiveness of the proposed method.

scholarly journals A probabilistic robust mixed H2/H∞ fuzzy control method for hypersonic vehicles based on reliability theory

2018 ◽  
Vol 15 (1) ◽  
pp. 172988141775415 ◽  
Author(s):  
Xiaomeng Yin ◽  
Xinming Li ◽  
Lei Liu ◽  
Yongji Wang ◽  
Xing Wei
Keyword(s):  
Fuzzy Control ◽  
Flight Control ◽  
Control Method ◽  
Fuzzy Controller ◽  
Fuzzy Model ◽  
Control Design ◽  
Hypersonic Vehicle ◽  
Linear Matrix ◽  
Hypersonic Vehicles ◽  
Robust Fuzzy Controller

Achieving balance between robustness and performance is always a challenge in the hypersonic vehicle flight control design. In this research, we focus on dealing with uncertainties of the fuzzy control system from the viewpoint of reliability. A probabilistic robust mixed H2/ H∞ fuzzy control method for hypersonic vehicles is presented by describing the uncertain parameters as random variables. First, a Takagi–Sugeno fuzzy model is employed for the hypersonic vehicle nonlinear dynamics characteristics. Next, a robust fuzzy controller is developed by solving a reliability-based multi-objective linear matrix inequality optimization problem, in which the H2/ H∞ performance is optimized under the condition that the system is robustly reliable to uncertainties. By this method, the system performance and reliability can be taken into account simultaneously, which reduces the conservatism in the robust fuzzy control design. Finally, simulation results of a hypersonic vehicle demonstrate the feasibility and effectiveness of the presented method.

scholarly journals Improved T-S Fuzzy Control for Uncertain Time-Delay Coronary Artery System

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-11
Author(s):  
Zhenyu Zhu ◽  
Zhanshan Zhao ◽  
Haoliang Cui ◽  
Fengdong Shi
Keyword(s):  
Coronary Artery ◽  
Fuzzy Controller ◽  
Fuzzy Model ◽  
Practical Significance ◽  
Linear Matrix ◽  
System State ◽  
Fuzzy Models ◽  
The Stability ◽  
Uncertain Time ◽  
Takagi Sugeno

This paper is based on the Takagi-Sugeno (T-S) fuzzy models to construct a coronary artery system (CAS) T-S fuzzy controller and considers the uncertainties of system state parameters in CAS. We propose the fuzzy model of CAS with uncertainties. By using T-S fuzzy model of CAS and the use of parallel distributed compensation (PDC) concept, the same fuzzy set is assigned to T-S fuzzy controller. Based on this, a PDC controller whose fuzzy rules correspond to the fuzzy model is designed. By constructing a suitable Lyapunov-Krasovskii function (LKF), the stability conditions of the linear matrix inequality (LMI) are exported. Simulation results show that the method proposed in this paper is correct and effective and has certain practical significance.

scholarly journals Robust Fuzzy Control for Fractional-Order Uncertain Hydroturbine Regulating System with Random Disturbances

2016 ◽  
Vol 2016 ◽  
pp. 1-11
Author(s):  
Fengjiao Wu ◽  
Guitao Zhang ◽  
Zhengzhong Wang
Keyword(s):  
Fuzzy Control ◽  
Fractional Order ◽  
Matrix Theory ◽  
Control Method ◽  
Interval Matrix ◽  
Linear Matrix ◽  
Uncertain Parameters ◽  
Matrix Inequalities ◽  
Random Disturbances ◽  
The Stability

The robust fuzzy control for fractional-order hydroturbine regulating system is studied in this paper. First, the more practical fractional-order hydroturbine regulating system with uncertain parameters and random disturbances is presented. Then, on the basis of interval matrix theory and fractional-order stability theorem, a fuzzy control method is proposed for fractional-order hydroturbine regulating system, and the stability condition is expressed as a group of linear matrix inequalities. Furthermore, the proposed method has good robustness which can process external random disturbances and uncertain parameters. Finally, the validity and superiority are proved by the numerical simulations.

Fuzzy Control of a Class of Discrete-Time Fuzzy Bilinear Systems with Time-Delay

2012 ◽  
Vol 482-484 ◽  
pp. 1881-1885
Author(s):  
Jian Hu Jiang ◽  
Chao Wu ◽  
Yun Wang Ge ◽  
Li Jun Song
Keyword(s):  
Discrete Time ◽  
Sufficient Conditions ◽  
Bilinear System ◽  
Stability Control ◽  
Linear Matrix ◽  
Time Varying ◽  
Matrix Inequalities ◽  
Time Varying Delay ◽  
The Stability ◽  
Varying Delay

The stability control problem is considered for a class of discrete-time T-S fuzzy bilinear system with time-varying delay in both state and input. Based on the parallel distribute compensation (PDC) scheme, some sufficient conditions are derived to guarantee the global asymptotically stability of the overall fuzzy system, which are represented in terms of matrix inequality. The corresponding controller can be obtained by solving a set of linear matrix inequalities. Finally, a simulation example shows that the approach is effective.

scholarly journals Variance and Passivity Constrained Fuzzy Control for Nonlinear Ship Steering Systems with State Multiplicative Noises

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Wen-Jer Chang ◽  
Bo-Jyun Huang
Keyword(s):  
Fuzzy Control ◽  
Control Method ◽  
Fuzzy Controller ◽  
Sufficient Conditions ◽  
Fuzzy Model ◽  
Lyapunov Theory ◽  
Linear Matrix ◽  
Multiplicative Noises ◽  
Ship Steering ◽  
The Matrix

The variance and passivity constrained fuzzy control problem for the nonlinear ship steering systems with state multiplicative noises is investigated. The continuous-time Takagi-Sugeno fuzzy model is used to represent the nonlinear ship steering systems with state multiplicative noises. In order to simultaneously achieve variance, passivity, and stability performances, some sufficient conditions are derived based on the Lyapunov theory. Employing the matrix transformation technique, these sufficient conditions can be expressed in terms of linear matrix inequalities. By solving the corresponding linear matrix inequality conditions, a parallel distributed compensation based fuzzy controller can be obtained to guarantee the stability of the closed-loop nonlinear ship steering systems subject to variance and passivity performance constraints. Finally, a numerical simulation example is provided to illustrate the usefulness and applicability of the proposed multiple performance constrained fuzzy control method.

scholarly journals Control Strategies for the Grid Side Converter in a Wind Generation System Based on a Fuzzy Approach

2018 ◽  
Vol 28 (2) ◽  
pp. 323-333 ◽  
Author(s):  
Naziha Harrabi ◽  
Maher Kharrat ◽  
Abdel Aitouche ◽  
Mansour Souissi
Keyword(s):  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Control Strategies ◽  
Fuzzy Model ◽  
Synchronous Generator ◽  
Linear Matrix ◽  
Fuzzy Approach ◽  
The Stability ◽  
Grid Side ◽  
Grid Side Converter

Abstract Two techniques for the control of a grid side converter in a wind energy conversion system. The system is composed of a fixed pitch angle wind turbine followed by a permanent magnet synchronous generator and power electronic converters AC-DC-AC. The main interest is in how to control the inverter in order to ensure the stability of the DC link voltage. Two control methods based on the fuzzy approach are applied and compared. First, a direct Mamdani fuzzy logic controller is presented. Then, a T-S fuzzy controller is elaborated based on a T-S fuzzy model. The Lyapunov theorem and H-infinity performance are exploited for stability analysis. Besides, the feedback controller gains are determined using linear matrix inequality tools. Simulation results are derived in order to prove the robustness of the proposed control algorithms and to compare their performances.

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