With the arrival of the new era,people love life and cherish the present life more,so they pay more and more attention to the security issues.Nowadays,the scale and complexity of dynamic control system are getting higher and higher.Once failure or other unexpected factors occur,the consequences should not be underestimated.It may not only cause serious economic loss,but even endanger life.Therefore,how to quickly and effectively locate and sense the size of the fault is the first step to ensure the normal and orderly operation of the control system,the question is the root of our research.The fault estimation method studied in this thesis is an effective means to accurately perceive faults and ensure the safe and reliable operation of the system,which has attracted extensive attention from many scholars recently.Fault estimation is the basis of fault-tolerant control,and the two complement each other to provide a strong guarantee for the safe operation of the system。In this thesis,the problem of fault estimation and fault-tolerant control for a class of Lipschitz nonlinear systems with actuator faults is studied:(1)The problem of fault estimation based adaptive observer for a class of nonlinear systems with Lipschitz nonlinearities and faults is studied.An adaptive observer based on intermediate variables is proposed(IAO),which makes full use of the output and its derivative information,and can estimate the faults and states of the system very well.Moreover,the designed observer can be reduced to a lower triangular estimation observer and performs better than the comprehensive estimation observer in the related literature.Finally,based on this observer,a more generalized error dynamics is derived,which reduces the conservatism of the stability condition.A uniform final bounded stability condition for the estimation error dynamics is given using linear matrix inequalities.Numerical examples illustrate the effectiveness and advantages of the proposed method.(2)For a class of locally nonlinear T-S fuzzy systems with faults,the traditional adaptive observation is improved,an adaptive observer based on lower triangular matrix transformation is proposed(LTAO),which improves the traditional adaptive observer.The proposed observer can not only be reduced to the traditional adaptive observer and intermediate estimator,but also performs better than the lower triangular estimator and the synthetic estimator proposed in the recent related literature.Moreover,the observer makes full use of the output derivative information and effectively improves the accuracy and efficiency of fault estimation.In addition,based on the improved adaptive observer,a more generalized error dynamics is derived,so that the stability condition of the error dynamics of is less conservative.Finally,the conditions obtained based on linear matrix inequalities guarantee uniform bounded stability of the error dynamics.Numerical examples show the effectiveness and superiority of the proposed method. |