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 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.

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.

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.

Robust-Optimal Fuzzy Model-Based Control of Flexible Spacecraft With Actuator Constraint

2016 ◽  
Vol 138 (9) ◽  
Author(s):  
Chokri Sendi ◽  
Mohammad A. Ayoubi
Keyword(s):  
Vibration Suppression ◽  
Fuzzy Controller ◽  
Fuzzy Model ◽  
Lyapunov Stability Theory ◽  
Flexible Spacecraft ◽  
Linear Matrix ◽  
Nonlinear Controller ◽  
Model Based ◽  
Stability Performance ◽  
Robust Fuzzy Controller

This paper presents a robust-optimal fuzzy controller for position and attitude stabilization and vibration suppression of a flexible spacecraft during antenna retargeting maneuver. The fuzzy controller is based on Takagi–Sugeno (T–S) fuzzy model and uses the parallel distributed compensator (PDC) technique to quadratically stabilize the closed-loop system. The proposed controller is robust to parameter and unstructured uncertainties of the model. We improve the performance and the efficiency of the controller by minimizing the upper bound of the actuator's amplitude and maximizing the uncertainties terms included in the T–S fuzzy model. In addition to actuator amplitude constraint, a fuzzy model-based observer is considered for estimating unmeasurable states. Using Lyapunov stability theory and linear matrix inequalities (LMIs), we formulate the problem of designing an optimal-robust fuzzy controller/observer with actuator amplitude constraint as a convex optimization problem. Numerical simulation is provided to demonstrate and compare the stability, performance, and robustness of the proposed fuzzy controller with a baseline nonlinear controller.

Shared Fuzzy Control of Multiple Quadrotor UAVs With Time-Dependent Delay and Bounded Control-Input Constraint

2015 ◽  
Author(s):  
Mark D. Johnson ◽  
Mohammad A. Ayoubi
Keyword(s):  
Fuzzy Control ◽  
Attitude Control ◽  
Fuzzy Controller ◽  
Equations Of Motion ◽  
Fuzzy Model ◽  
Linear Matrix ◽  
Control Input ◽  
Maximum Magnitude ◽  
Time Varying ◽  
Bounded Control

We propose a shared fuzzy controller for position and attitude control of multiple quadrotor unmanned aerial vehicles (UAVs). Using the nonlinear governing equations of motion and kinematics of a quadrotor, we develop a Takagi-Sugeno (T-S) fuzzy model for a quadrotor. Then, we consider time-varying delays due to wireless connectioninto the T-S fuzzy model. We use the sufficient stability condition based on the Lyapunov-Krasovskii stability theorem and the parallel distributed compensation (PDC) technique to determine the fuzzy control law. For practical purposes, we include actuator amplitude constraint into the design process. The problem of designing a shared fuzzy controller is cast in the form of linear matrix inequalities (LMIs). A feasible solution region is found in terms of maximum magnitude and rate of time-varying delay. In the end, the stability, performance, and robustness of the proposed shared fuzzy controller are examined via numerical simulation.

scholarly journals RobustH∞Fuzzy Control for Nonlinear Discrete-Time Stochastic Systems with Markovian Jump and Parametric Uncertainties

2014 ◽  
Vol 2014 ◽  
pp. 1-11
Author(s):  
Huiying Sun ◽  
Long Yan
Keyword(s):  
Fuzzy Control ◽  
Discrete Time ◽  
Stochastic Systems ◽  
Design Method ◽  
Fuzzy Model ◽  
Control Design ◽  
Linear Matrix ◽  
Parametric Uncertainties ◽  
Markovian Jump ◽  
Parameter Uncertainties

The paper mainly investigates theH∞fuzzy control problem for a class of nonlinear discrete-time stochastic systems with Markovian jump and parametric uncertainties. The class of systems is modeled by a state space Takagi-Sugeno (T-S) fuzzy model that has linear nominal parts and norm-bounded parameter uncertainties in the state and output equations. AnH∞control design method is developed by using the Lyapunov function. The decoupling technique makes the Lyapunov matrices and the system matrices separated, which makes the control design feasible. Then, some strict linear matrix inequalities are derived on robustH∞norm conditions in which both robust stability andH∞performance are required to be achieved. Finally, a computer-simulated truck-trailer example is given to verify the feasibility and effectiveness of the proposed design method.

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.

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.

A Fuzzy Control Approach for the Coordinated-Level Control of the Modular-HTGR-Based Nuclear Steam Supplying System

2016 ◽  
Author(s):  
Yue Yuan ◽  
Xiaojin Huang
Keyword(s):  
Fuzzy Control ◽  
Control Method ◽  
Fuzzy Controller ◽  
Fuzzy Model ◽  
Energy System ◽  
Inherent Safety ◽  
Level Control ◽  
Control Approach ◽  
Basic Ideas ◽  
Safety Features

As one of the most popular Generation IV nuclear energy system, High Temperature Gas Cooled Reactor (HTGR) has outstanding inherent safety features. However, the nonlinearity and complexity of the modular-HTGR-based nuclear steam supplying system (NSSS) has put higher requirements to its control system. Based on the basic ideas and theories of fuzzy system, fuzzy control method provides a powerful tool to the control of nonlinear systems. This paper built the T-S fuzzy model of the modular-HTGR-based nuclear steam supplying system (NSSS), and designed the steam temperature T-S fuzzy controller using the parallel distributed compensation (PDC) method. Simulation shows that the designed T-S fuzzy controller has a better effect than the traditional PID control method.

Laser-range-finder localization based fuzzy control for mobile robots

2017 ◽  
Vol 34 (7) ◽  
pp. 2409-2421 ◽  
Author(s):  
Chung-Hsun Sun ◽  
Sheng-Kai Huang ◽  
Hsuan Chen ◽  
Cheng-Wei Ye ◽  
Yin-Tien Wang ◽  
...  
Keyword(s):  
Fuzzy Control ◽  
Mobile Robot ◽  
Fuzzy Controller ◽  
Kinematic Model ◽  
Fuzzy Model ◽  
Control Design ◽  
Laser Range Finder ◽  
Content Type ◽  
Practical Limitation ◽  
Lyapunov Stabilization

Purpose Based on laser-range-finder (LRF) sensing, the control design of location and orientation stabilization for the mobile robot is investigated. However, the practical limitation of the LRF sensing is usually ignored in the control design, which leads to incorrect localization and unexpected control results. The purpose of this study is to design the fuzzy controller subject to the practical limitation on the LRF-based localization for a differentially driven wheeled mobile robot. Design/methodology/approach First, the Takagi–Sugeno (T-S) fuzzy model is derived from the polar kinematic model of a differentially driven mobile robot. Then, the fuzzy controller is designed to the derived T-S fuzzy kinematic model in accordance with the Lyapunov stabilization theorem. The derived Lyapunov stabilization conditions for the fuzzy control design are expressed as the linear matrix inequality (LMI) form and effectively solved by LMI tools. The practical limitation on the LRF-based localization is also expressed as the LMI form and simultaneously solved with the control design. Finding The location and posture stabilization experiments are carried out on a mobile robot with LRF-based localization to prove the effectiveness of the proposed T-S fuzzy model-based control design. Furthermore, the ground truth experiment evaluates the accuracy of LRF-based localization. Originality/value The contribution of this study is to develop the fuzzy control law for a differentially driven wheeled mobile robot under the practical limitation on LRF-based localization. The proposed control design can be applied to other robots with practical limitations on the sensors.

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