Fault Diagnosis And Fault Tolerant Control For Nonlinear Systems With High Input Powers

Since the 21st century,with the development of science and technology and the continuous improvement of modern intelligent living standards,the safety of equipment production becomes more and more important,therefore,how to improve the efficiency and accuracy of equipment operation has been widely concerned by people.However,system faults,such as actuator faults,sensor faults,etc.,are inevitable in practical engineering.These faults will affect the normal operation of the system to a certain extent,prevent the system from achieving specific performance indicators,and even lead to the system instability.Therefore,fault diagnosis and fault-tolerant control of dynamic system is particularly important,and has attracted the attention of experts and scholars,and its related research is gradually deepening.However,the input power considered in the existing relevant studies is equal to "1".However,in practical applications,the input will change due to actuator failure and other factor,that is,the power of the system input is greater than"1".In this paper,the input power is called high input power,and this kind of fault is called input power fault.In this case,the existing control method will be difficult to apply,so a new control method must be designed to achieve the control objective.Because the nonlinear system with high input power studied in this paper has complex structure and involves many types of fault,the research on fault diagnosis and fault tolerance control of nonlinear systems with high input powers is of practical significance.In this paper,two cases:input power is known or unknown,are considered respectively for the high-order nonlinear system.For the actuator fault and the input power fault,the corresponding fault diagnosis and fault tolerance control schemes are proposed respectively by using adaptive control and neural network methods.The main research contents of this paper are summarized as follows:Firstly,the problem of fault detection and isolation is studied for a class of high order dynamic systems with actuator faults.First,a fault detection observer and a fault decision mechanism are constructed to realize timely fault detection.Then,a series of fault isolation observers are designed and the fault isolation algorithm is given.Based on Lyapunov stability theory,the stability of dynamic observation error is analyzed.Finally,simulation results verify the effectiveness of the proposed method.Secondly,the problems of stability control,fault detection and estimation are studied for a class of uncertain high-order nonlinear systems with unknown system powers.Firstly,a novel adaptive control method is designed to make the system stable and the state converges to the origin.Then,fault detection observer is constructed to detect the fault in time.In addition,fault estimation observer is designed so that the fault can be estimated timely and accurately.By comparing the results of the existing literatures,this method overcomes some errors and relaxes some assumptions.Furthermore,the new observers do not require the condition that input powers should be known,which is necessary in the classical observer design.Finally,an example is given to validate the theoretical results.Thirdly,adaptive fault-tolerant stability control is studied for a class of SISO nonlinear uncertain systems affected by power faults and disturbances.A new adaptive fault-tolerant control strategy is designed by using neural networks to ensure that the closed-loop system is asymptotic stability and all closed-loop signals converge to the origin.The unknown input power fault can be estimated online.In addition,the strategy relaxes some of the assumptions presented in the existing results.Simulation results show that the strategy is effective.