scholarly journals A Control Approach Based on Observers of State and Uncertainty for a Class of Takagi–Sugeno Fuzzy Models

Author(s):  
Jun Zhao ◽  
Hugang Han ◽  
◽  

Although the Takagi–Sugeno fuzzy model is effective for representing the dynamics of a plant to be controlled, two main questions arise when using it just as other models: 1) how to deal with the gap, which is referred to as uncertainty in this study, between the model and the concerned plant, and how to estimate the state information when it cannot be obtained directly, especially with the existence of uncertainty; 2) how to design a controller that guarantees a stable control system where only the estimated state is available and an uncertainty exists. While the existing studies cannot effectively observe the state and the resulting control systems can only be managed to be uniformly stable, this study first presents a state observer capable of precisely estimating the state regardless of the existence of uncertainty. Then, based on the state observer, an uncertainty observer is derived, which can track the trajectory of uncertainty whenever it occurs in a real system. Finally, a controller based on both observers is presented, which guarantees the asymptotic stability of the resulting control system.

Energies ◽  
2019 ◽  
Vol 12 (11) ◽  
pp. 2221 ◽  
Author(s):  
Himanshukumar R. Patel ◽  
Vipul A. Shah

This paper deals with a methodical design approach of fault-tolerant controller that gives assurance for the the stabilization and acceptable control performance of the nonlinear systems which can be described by Takagi–Sugeno (T–S) fuzzy models. Takagi–Sugeno fuzzy model gives a unique edge that allows us to apply the traditional linear system theory for the investigation and blend of nonlinear systems by linear models in a different state space region. The overall fuzzy model of the nonlinear system is obtained by fuzzy combination of the all linear models. After that, based on this linear model, we employ parallel distributed compensation for designing linear controllers for each linear model. Also this paper reports of the T–S fuzzy system with less conservative stabilization condition which gives decent performance. However, the controller synthesis for nonlinear systems described by the T–S fuzzy model is a complicated task, which can be reduced to convex problems linking with linear matrix inequalities (LMIs). Further sufficient conservative stabilization conditions are represented by a set of LMIs for the Takagi–Sugeno fuzzy control systems, which can be solved by using MATLAB software. Two-rule T–S fuzzy model is used to describe the nonlinear system and this system demonstrated with proposed fault-tolerant control scheme. The proposed fault-tolerant controller implemented and validated on three interconnected conical tank system with two constraints in terms of faults, one issed to build the actuator and sond is system component (leak) respectively. The MATLAB Simulink platform with linear fuzzy models and an LMI Toolbox was used to solve the LMIs and determine the controller gains subject to the proposed design approach.


2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Guang He ◽  
Jie Li ◽  
Peng Cui ◽  
Yun Li

The control problem for the networked suspension control system of maglev train with random induced time delay and packet dropouts is investigated. First, Takagi-Sugeno (T-S) fuzzy models are utilized to represent the discrete-time nonlinear networked suspension control system, and the parameters uncertainties of the nonlinear model have also been taken into account. The controllers take the form of parallel distributed compensation. Then, a sufficient condition for the stability of the networked suspension control system is derived. Based on the criteria, the state feedback fuzzy controllers are obtained, and the controller gains can be computed by using MATLAB LMI Toolbox directly. Finally, both the numerical simulations and physical experiments on the full-scale single bogie of CMS-04 maglev train have been accomplished to demonstrate the effectiveness of this proposed method.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ayaz Ahmed Hoshu ◽  
Liuping Wang ◽  
Alex Fisher ◽  
Abdul Sattar

PurposeDespite of the numerous characteristics of the multirotor unmanned aircraft systems (UASs), they have been termed as less energy-efficient compared to fixed-wing and helicopter counterparts. The purpose of this paper is to explore a more efficient multirotor configuration and to provide the robust and stable control system for it.Design/methodology/approachA heterogeneous multirotor configuration is explored in this paper, which employs a large rotor at the centre to provide majority of lift and three small tilted booms rotors to provide the control. Design provides the combined characteristics of both quadcopters and helicopters in a single UAS configuration, providing endurance of helicopters keeping the manoeuvrability, simplicity and control of quadcopters. In this paper, rotational as well as translational dynamics of the multirotor are explored. Cascade control system is designed to provide an effective solution to control the attitude, altitude and position of the rotorcraft.FindingsOne of the challenging tasks towards successful flight of such a configuration is to design a stable and robust control system as it is an underactuated system possessing complex non-linearities and coupled dynamics. Cascaded proportional integral (PI) control approach has provided an efficient solution with stable control performance. A novel motor control loop is implemented to ensure enhanced disturbance rejection, which is also validated through Dryden turbulence model and 1-cosine gust model.Originality/valueRobustness and stability of the proposed control structure for such a dynamically complex UAS configuration is demonstrated with stable attitude and position performance, reference tracking and enhanced disturbance rejection.


A fundamental diagram of a control system for missiles of various classes is investigated. A functional diagram of a control system with an intelligent component for long-range aerodynamic rockets returning to the atmosphere is developed. It is proposed to use in the control loop an ensemble of a priori missile models and models of external influences. It is proposed to improve the accuracy of control systems with an intelligent component by increasing the degree of controllability of the state variables for a priori models. The most convenient numerical criterion of controllability degree for of the state variables of the models is presented. The results of mathematical modeling showed a slight increase in the efficiency of missile control with an increase in the degree of controllability of the pitch angle by changing the coefficients of the control matrix. Keywords rocket; control system; intelligent component; an action acceptor; a priori model; controllability; degree of controllability; management efficiency


Sensors ◽  
2019 ◽  
Vol 20 (1) ◽  
pp. 27 ◽  
Author(s):  
Hao Wang ◽  
Shousheng Xie ◽  
Bin Zhou ◽  
Weixuan Wang

The fault-tolerant robust non-fragile H∞ filtering problem for networked control systems with sensor failures is studied in this paper. The Takagi-Sugeno fuzzy model which can appropriate any nonlinear systems is employed. Based on the model, a filter which can maintain stability and H∞ performance level under the influence of gain perturbation of the filter and sensor failures is designed. Moreover, the gain matrix of sensor failures is converted into a dynamic interval to expand the range of allowed failures. And the sufficient condition for the existence of the desired filter is derived in terms of linear matrix inequalities (LMIs) solutions. Finally a simulation example is given to illustrate the effectiveness of the proposed method.


Author(s):  
Xiuchun Luan ◽  
Jie Zhou ◽  
Yu Zhai

A state differential feedback control system based Takagi-Sugeno (T-S) fuzzy model is designed for load-following operation of nonlinear nuclear reactor whose operating points vary within a wide range. Linear models are first derived from the original nonlinear model on several operating points. Next the fuzzy controller is designed via using the parallel distributed compensation (PDC) scheme with the relative neutron density at the equilibrium point as the premise variable. Last the stability analysis is given by means of linear matrix inequality (LMI) approach, thus the control system is guaranteed to be stable within a large range. The simulation results demonstrate that the control system works well over a wide region of operation.


Author(s):  
Ben T. Zinn

This paper reviews the state of the art of active control systems (ACS) for gas turbine combustors. Specifically, it discusses the manner in which ACS can improve the performance of combustors, the architecture of such ACS, and the designs and promising performance of ACS that have been developed to control combustion instabilities, lean blowout and pattern factor. The paper closes with a discussion of research needs, with emphasis on the integration of utilized engine ACS, health monitoring and prognostication systems into a single control system that could survive in the harsh combustor environment.


2018 ◽  
Vol 2018 ◽  
pp. 1-14
Author(s):  
Chang Che ◽  
Jiayao Peng ◽  
Tao Zhao ◽  
Jian Xiao ◽  
Jie Zhou

This paper focuses on the problem of nonlinear systems with input and state delays. The considered nonlinear systems are represented by Takagi-Sugeno (T-S) fuzzy model. A new state feedback control approach is introduced for T-S fuzzy systems with input delay and state delays. A new Lyapunov-Krasovskii functional is employed to derive less conservative stability conditions by incorporating a recently developed Wirtinger-based integral inequality. Based on the Lyapunov stability criterion, a series of linear matrix inequalities (LMIs) are obtained by using the slack variables and integral inequality, which guarantees the asymptotic stability of the closed-loop system. Several numerical examples are given to show the advantages of the proposed results.


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