Research On Intelligence Fault Diagnosis And Fault-tolerant Control Methods Of Complex Nonlinear System

Nonlinear is the inherent attribute of the mechanical system dynamics. Largemechanical system is a complex nonlinear dynamic system, it has uncertainty, nonlinear,time variation etc, fault condition is complex, and interference factors are great.Mechanical fault diagnosis methods based on linear theory have great limitations, it isdifficult to meet the practical needs for diagnosis. Therefore, development of complexnonlinear system fault diagnosis and fault tolerant control method research has importanttheory significance and practical application value. In this thesis, for complex nonlinearsystem, some kinds of different intelligent fault diagnosis methods are studied, and severalfault-tolerant control methods of nonlinear system are put forwarded. The main contentsof this thesis are as follows:In this thesis, wavelet transformation and chaos theory are combined with neuralnetwork for fault diagnosis. In fault diagnosis, first, wavelet analysis is used in signalde-noising pretreatment, the fault information components are detected effectively, and thecorrelation dimension and other chaotic characteristics are used to depict the fault featuresof vibration signal, the status of mechanical equipment are classified and recognized, thismethod overcomes the difficulty of the traditional method in fault signal feature extractionand analysis. Next, the network model of a wavelet neural network is put forwarded, andusing improved genetic algorithm who has global search capability on the optimization ofthe weights and thresholds, avoiding the disadvantages of BP algorithm, and throughsimulation experiment, the feasibility of this algorithm is proved.In this thesis, fault tolerant control method of a kind of nonlinear time-delay systemis put forwarded. For the nonlinear time-delay system and nonlinear switching time-delaysystem with fault, the adaptive fault estimation algorithm is adopted, and nonlinear systemadaptive observer based on the algorithm is designed, and fault-tolerant controller of faultsystem is designed according to adaptive estimation of the faults, and through thelyapunov boundedness theory, effectiveness of this algorithm are proved. Finally, thesimulation experiments show that the algorithm is feasible. In this thesis, fault tolerant control method of a kind of time-delay neutral system isput forwarded. For the time-delay neutral system with fault, the adaptive fault estimationalgorithm is adopted, and whole dimension observer of time-delay neutral system basedon output feedback is designed, and through the lyapunov boundedness theory,effectiveness of this algorithm are proved. Finally, the simulation experiments show thatthe algorithm is feasible.In the thesis, adaptive fault tolerant control method of a kind of non-affine nonlinearneural network is put forwarded. Because of the nonlinear approximation ability of neuralnetwork, neural network is used to estimate faults of nonlinear system, the neural networkfault diagnosis method is designed, and neural network controller of non-affine nonlinearsystem is designed according to the approximation ability of neural network, the weightvalues of neural network are online adjusted through the adaptive algorithm, based onLyapunov theory, the closed-loop system tracking error is uniform bounded stable isproved. Finally, the effectiveness of this adaptive algorithm is verified through thenumerical simulation results.