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.

scholarly journals State feedback fuzzy-model-based control for Markovian jump nonlinear systems

2004 ◽  
Vol 15 (3) ◽  
pp. 279-290 ◽  
Author(s):  
Natache S. D. Arrifano ◽  
Vilma A. Oliveira
Keyword(s):  
Nonlinear Systems ◽  
Fuzzy System ◽  
System Modeling ◽  
Fuzzy Model ◽  
Control Design ◽  
Linear Matrix ◽  
Markovian Jump ◽  
Stabilizing Controller ◽  
Model Based Control ◽  
Model Based

This paper deals with the fuzzy-model-based control design for a class of Markovian jump nonlinear systems. A fuzzy system modeling is proposed to represent the dynamics of this class of systems. The structure of the fuzzy system is composed of two levels, a crisp level which describes the Markovian jumps and a fuzzy level which describes the system nonlinearities. A sufficient condition on the existence of a stochastically stabilizing controller using a Lyapunov function approach is presented. The fuzzy-model-based control design is formulated in terms of a set of linear matrix inequalities. Simulation results for a single-machine infinite-bus power system which is modeled as a Markovian jump nonlinear system in the infinite-bus voltage are presented to illustrate the applicability of the technique.

Delay-Dependent Robust Control for Discrete-Time Uncertain Stochastic Systems With Time-Varying Delays

2017 ◽  
Vol 139 (10) ◽  
Author(s):  
Cheung-Chieh Ku ◽  
Guan-Wei Chen
Keyword(s):  
Robust Control ◽  
Discrete Time ◽  
Stochastic Systems ◽  
Design Method ◽  
Sufficient Conditions ◽  
Jensen Inequality ◽  
Linear Matrix ◽  
Time Varying ◽  
Gain Scheduled Controller ◽  
Delay Dependent

This paper investigates a delay-dependent robust control problem of discrete-time uncertain stochastic systems with delays. The uncertainty considered in this paper is time-varying but norm-bounded, and the delays are considered as interval time-varying case for both state and input. According to the considerations of uncertainty, stochastic behavior, and time delays, the problem considered in this paper is more general than the existing works for uncertain stochastic systems. Via the proposed Lyapunov–Krasovskii function, some sufficient conditions are derived into the extended linear matrix inequality form. Moreover, Jensen inequality and free matrix equation are employed to reduce conservatism of those conditions. Through using the proposed design method, a gain-scheduled controller is designed to guarantee asymptotical stability of uncertain stochastic systems in the sense of mean square. Finally, two numerical examples are provided to demonstrate applicability and effectiveness of the proposed design method.

Fuzzy Control for Nonlinear Uncertain T-S Fuzzy Systems with Time-Varying Delays

2013 ◽  
Vol 341-342 ◽  
pp. 668-673
Author(s):  
Yi Min Li ◽  
Yuan Yuan Li
Keyword(s):  
Stability Analysis ◽  
Discrete Time ◽  
Fuzzy Model ◽  
Optimization Techniques ◽  
Linear Matrix ◽  
Time Varying ◽  
Parameter Uncertainties ◽  
Lmi Optimization ◽  
System A ◽  
The Stability

This paper studies the stability analysis of discrete time-varying system with parameter uncertainties and disturbances. The system under consideration is subject to time-varying non-bounded parameter uncertainties in both the state and measured output matrices. To facilitate the stability analysis, the T-S fuzzy model is employed to represent the discrete-time nonlinear system. A fuzzy observer is used to guarantee the Lyapunov stability of the closed-loop system and reduces the effect of the disturbance input on the controlled output to a prescribed level for all admissible uncertainties. The control and observer matrices can be obtained by directly solving a set of linear matrix inequality (LMI) via the existing LMI optimization techniques. Finally, an example is provided to demonstrate the effectiveness of the proposed approach.

scholarly journals Delay-Dependent RobustH∞Filtering of the Takagi-Sugeno Fuzzy Stochastic Systems

2013 ◽  
Vol 2013 ◽  
pp. 1-12
Author(s):  
Ze Li ◽  
Xin-Hao Yang
Keyword(s):  
Stochastic Systems ◽  
Design Method ◽  
Linear Matrix ◽  
Mean Square ◽  
Matrix Inequalities ◽  
Parameter Uncertainties ◽  
Mean Square Stability ◽  
Error System ◽  
Delay Dependent ◽  
Takagi Sugeno

This paper is concerned with the problem of the robustH∞filtering for the Takagi-Sugeno (T-S) fuzzy stochastic systems with bounded parameter uncertainties. For a given T-S fuzzy stochastic system, this paper focuses on the stochastically mean-square stability of the filtering error system and theH∞performance level of the output error and the disturbance input. The design method for delay-dependent filter is developed based on linear matrix inequalities. Finally, the effectiveness of the proposed methods is substantiated with an illustrative example.

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.

OBSERVER-BASED FUZZY CONTROL DESIGN FOR DISCRETE-TIME T-S FUZZY BILINEAR SYSTEMS

2013 ◽  
Vol 21 (03) ◽  
pp. 435-454 ◽  
Author(s):  
JIANGRONG LI ◽  
JUNMIN LI ◽  
ZHILE XIA
Keyword(s):  
Fuzzy Control ◽  
Discrete Time ◽  
Control Design ◽  
Bilinear System ◽  
Single Step ◽  
Bilinear Systems ◽  
Linear Matrix ◽  
Fuzzy Observer ◽  
Nonlinear Minimization ◽  
The Stability

This paper is concerned with the problem of observer-based fuzzy control design for discrete-time T-S fuzzy bilinear systems. Based on the piecewise quadratic Lyapunov function (PQLF), the piecewise fuzzy observer-based controllers are designed for T-S fuzzy bilinear systems. It is shown that the stability for discrete T-S fuzzy bilinear system can be established if there exists a PQLF can be constructed and the fuzzy observer-based controller can be obtained by solving a set of nonlinear minimization problem involving linear matrix inequalities(LMIs) constraints. An iterative algorithm making use of sequential linear programming matrix method (SLPMM) to derive a single-step LMI condition for fuzzy observer-based control design. Finally, an illustrative example is provided to demonstrate the effectiveness of the results proposed in this paper.

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.

scholarly journals RobustH∞Filtering for Uncertain Discrete-Time Fuzzy Stochastic Systems with Sensor Nonlinearities and Time-Varying Delay

2012 ◽  
Vol 2012 ◽  
pp. 1-25 ◽  
Author(s):  
Mingang Hua ◽  
Pei Cheng ◽  
Juntao Fei ◽  
Jianyong Zhang ◽  
Junfeng Chen
Keyword(s):  
Discrete Time ◽  
Stochastic Systems ◽  
Sufficient Conditions ◽  
Lyapunov Stability Theory ◽  
Linear Matrix ◽  
Time Varying ◽  
Parameter Uncertainties ◽  
Time Varying Delay ◽  
Error System ◽  
Varying Delay

The robust filtering problem for a class of uncertain discrete-time fuzzy stochastic systems with sensor nonlinearities and time-varying delay is investigated. The parameter uncertainties are assumed to be time varying norm bounded in both the state and measurement equations. By using the Lyapunov stability theory and some new relaxed techniques, sufficient conditions are proposed to guarantee the robustly stochastic stability with a prescribedH∞performance level of the filtering error system for all admissible uncertainties, sensor nonlinearities, and time-varying delays. These conditions are dependent on the lower and upper bounds of the time-varying delays and are obtained in terms of a linear matrix inequality (LMI). Finally, two simulation examples are provided to illustrate the effectiveness of the proposed methods.

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