Research On Fault Estimation Problems For Time-varying Delay T-S Fuzzy Systems

With the improvement of modern science and technology,the scale of control sys-tems and complexity is rapidly increasing.The higher demand for operational reliability and safety of the modern production system is the reason for generation and rapid de-velopment of the fault diagnosis technology.In actual production process,if a system failure occurs,the economic loss is difficult to estimate.Fault estimation can timely and accurately describe the fault,so further providing a quantitative fault information for fault diagnosis is particularly important.On the other hand,it has been demonstrated that T-S fuzzy model can be used to approximate any nonlinear systems on any degree of accuracy.In recent years,the analysis and synthesis of fault estimation methods for nonlinear sys-tem based on T-S fuzzy model have attracted great interest.However,due to the difficulty of quantitative analysis of fault estimation and lack of technical analysis methods,and the system is also affected by time delay,external disturbance and system uncertain factors,so there are still many problems to be solved further,such as for T-S fuzzy systems with interval time-varying delay,random time delay,mode-dependent time delay constraints,in the presence of external disturbances,there is a lack of effective roust fault estimation method to give the fault information.On the basis of the existing works,this dissertation is focused on the research of fault estimation problems for several different kinds of T-S fuzzy systems with time de-lays.Based on the iterative learning observer design method,the problem of fault esti-mation and fault-tolerant control for a class of interval time delay T-S fuzzy system is solved.Meanwhile,for a class of random time delay T-S fuzzy systems with unmea-surable premise variables,the actuator fault estimator and output feedback fault-tolerant controller based on iterative learning and adaptive method is investigated.For the T-S fuzzy systems with state time-varying delays,a new robust fault estimation method with less conservativeness is proposed.The robust estimator design method of estimating actu-ator fault is proposed for a class of time delay fuzzy descriptor systems.A robust adaptive fault estimator is given for the mode-dependent time delay fuzzy Markovian jumping sys-tems.Parts of the developed theories are applied to the fault estimation for cart inverted pendulum model,truck trailer system model and single-link robot arm model by simu-lations.Simulation results illustrate the advantages and effectiveness of our approaches.The main contents are outlined as follows:1.Based on the iterative learning and delay partitioning approach,the problem of ro-bust fault estimation and fault-tolerant control design scheme for a class of T-S fuzzy sys-tems is studied,which is subject to interval time-varying delay and external disturbances.First,by using improved delay partitioning approach,a novel iterative learning fault es-timation observer is constructed to achieve estimation of actuator fault.Then,based on the online estimation information,a fuzzy dynamic output feedback fault-tolerant con-troller considered interval time delay is designed to compensate for the impact of actu-ator faults,while guaranteeing that the closed-loop system is asymptotically stable with the prescribed H? performance.Moreover,all the obtained less conservative sufficient conditions for the existence of fault estimation observer and fault-tolerant controller are formulated in terms of linear matrix inequalities.Finally,the numerical examples and simulation results are presented to show the effectiveness and merits of the proposed methods.2.Two different methods of fault estimation and the fault-tolerant control problem for a class of random time delay T-S fuzzy systems with unmeasurable premise vari-able are concerned.Firstly,by taking the unmeasurable premise variables and actuator fault as auxiliary disturbance signal,and combining with the improved delay partition-ing approach,two robust fault estimation observers based on iterative learning algorithm and adaptive method are constructed and the sufficient conditions for the existence of observers are presented.Then,through the use of uncertain system approach,a fuzzy output feedback fault-tolerant controller with unmeasurable premise variables is designed to compensate for the impact of actuator fault,while guaranteeing that the closed-loop system is stable with the prescribed H? performance.Finally,the simulation examples show the effectiveness of proposed approach.3.The problem of robust fault estimation for a class T-S nonlinear systems with time-varying state delay is addressed.Under H? performance constraint,a fuzzy-augmented error dynamic system is proposed to enhance the performance of fault estimation for T-S nonlinear state delay models with actuator and sensor faults simultaneously.Based on Lyapunov function and the improved free-weighting approach,some less conservative sufficient conditions for the existence of fault estimation observer are given in terms of linear matrix inequalities,meanwhile,the obtained fault estimates can practically better depict the size and shape of the faults.Finally,three illustrative examples are given to illustrate the validity of the proposed design procedures.4.The problem of robust fault estimation for a class of T-S fuzzy singular systems with delay-dependent time delays is solved.First,based on the improved delay partition-ing approach,the admissible analysis for T-S fuzzy singular systems with interval time-varying delay and linear fractional uncertainties is investigated.Secondly,by considering the system fault as an auxiliary disturbance vector and constructing an appropriate fuzzy augmented system,the fault estimator existence criteria is obtained to guarantee the er-ror dynamic system is admissible and estimate the actuator and sensor fault at the same time.Then the numerical examples and simulation results illustrate the advantages and effectiveness of the proposed methods?5.The design scheme of actuator fault estimation for a class of T-S fuzzy Markovian jumping systems is studied,which is subject to interval mode-dependent time-varying delays and norm-bounded external disturbance.Based on the given fast adaptive esti-mation algorithm and by employing a novel Lyapunov-Krasovskii function candidate,in which two different Markovian stochastic process information are considered,an im-proved mode-dependent criterion for the existence of fault estimation observer is estab-lished to guarantee the error dynamic system to be stochastically stable with a prescribed H_? performance and reduce the conservatism of designing procedure at the same time.Finally,two numerical examples are given to show the effectiveness of the proposed method.Finally,the results of the dissertation are summarized and further research topics are pointed out.