Aihua Zhang

An intelligent particle filter for state estimation and fault detection

With the continuous development of computer science and control science, the complexity of the system also increased rapidly. Accordingly, people began to improve the security and stability of the systems, and fault diagnosis in time is an effectively method to reduce the loss of property. The reality systems are invariably more complex, nonlinear and non-Gaussian. The previous method cannot solve the problem very well. However, as an unique technology, the particle filter (PF) can apply to nonlinear and non-Gaussian systems effectively. The accuracy of state estimation is influenced by the particle impoverishment problem in the quintessential PF algorithm. In order to deal with the particle impoverishment, we propose an intelligent particle filter (IPF) algorithm which based on genetic algorithm optimization after analyzed the particle filter algorithm. The common PF is a special circumstances of IPF that relieves the particular parameters. Results of these two experimental applications of the IPF are given to illustrate it can increase the particles diversity and improve the state estimation results of fault diagnosis.

A novel intelligent particle filter for process monitoring

Particle filter (PF) serves as an effective method applied to the fault diagnosis of nonlinear and non-Gaussian systems. However, the result of state estimation is influenced by the particle impoverishment problem which is common in the typical PF algorithm. Based on the analysis of the PF algorithm, the general particle impoverishment problem is attributed to the deficiency of particle diversity. In this paper a novel intelligent particle filter (NIPF) is designed to deal with the problem of particle impoverishment by means of the genetic and adaptive strategy. The general PF can be regarded as a particular instance of NIPF. The experiment on the vertically falling body model shows that the NIPF can increase the particles diversity and improve the results of state estimation.

Research on amplifier performance evaluation based on feature double weighted support vector machine

An evaluation for amplifier performance based on feature double weighted support vector machine was proposed in this paper. The evaluation system structure was conformed, relied on the college analog electronic technology experiments, adopted the amplifier performance four indexes obtained via amplitude-frequency tester in one year to construct training set, and then to be four classifier evaluation based on FDWSVM. Experiment results show that this method can improve the parameter test precision and is suitable for the evaluation of electronic products.

Robust fault tolerant control for drive train in wind turbine systems with stochastic perturbations

To achieve reliable operation of wind energy conversion technology, this ρ aper develops a robust observer-based fault tolerant control technique for wind turbine drive train systems in presence of simultaneous unknown inputs, faults and Brownian perturbations. Integration of several advanced techniques, namely, augmented approach, unknown input observer method, and linear matrix inequaity, is employed to estimate the means of the system states and the considered faults robustly. Based on the estimates, robust fault tolerant control strategy is implemented to drive the system trajectory convergent and eliminate the effects of faults from both actuators and sensors successfully. The control gains are selected to guarantee the convergence of the means of system states and com pens ate for the de grad ation caused by concerned faults. The ob server gain is determined via a linear matrix inequality optimization such that the closed-loop system is stochastically input-to-state stable satisfying required robust performance. The desi gned observer-based fault tolerant control c an make the over all system work in a steady condition and the system outputs c an be compensated to successfully track the healthy outputs in fault-free c ases. Finally, the proposed fault estimation-based fault tolerant control method is applied to a drive train system of the 4.8 MW benchmark wind wind turbine to validate the effectiveness.

Robust fault estimation and fault tolerant control for Lipschitz nonlinear brownian systems

This paper investigates robust fault estimation and fault tolerant control problems for stochastic Lipschitz nonlinear systems subject to Brownian motions, unexpected faults and unknown inputs. Augmented system approach and unknown input observer are integrated to produce robust estimates of the means of the faults and the full system states simultaneously. Based on the well-designed fault estimation scheme, a robust fault tolerant control strategy is proposed to compensate faults, stabilize the closed loop system, and eliminate the effects of unknown inputs. Sufficient conditions are presented in terms of linear matrix inequalities for the overall closed-loop system composed of both states and error dynamics to guarantee the stability and robustness of the system. Furthermore, the systematic design procedure for the robust fault estimation and fault tolerant control scheme is addressed. Finally, simulation on a single joint robotic model is illustrated to validate the suggested methodologies.

A Semi-Supervision Fault Diagnosis Method Based on Attitude Information for a Satellite

The various faults that inevitably occur represent a primary issue in satellite on-orbit operation. Fault diagnosis is the first step in the fault control process. As a means to perform this step, a semi-supervision fault diagnosis method via attitude information is proposed for a satellite. This method combines static fusion with dynamic updating. The evidence concept is employed to obtain the fault information. It not only allows the detection of the slow change and failure with interference, but also confirms the optimal fusion and updating parameters via historical data. Numerical simulations, including static fusion diagnosis and dynamic updating diagnosis, are all presented with the proposed semi-supervision diagnosis methods to compare and prove the effectiveness of the proposed approach.

Satellite Attitude Control with Actuator Failure

A method of attitude stabilization control, based on observer design is proposed for an on-orbiting spacecraft in the presence of partial loss of actuator effectiveness, external disturbance and actuator control input saturation problem. In this approach, observer is employed to estimate the value of actuator fault, and a Backstepping attitude controller is then designed to achieve fault tolerant control and external disturbance rejection. The Lyapunov stability analysis shows that the closed-loop attitude system is guaranteed to be almost asymptotically stable. The simulation results show the effectiveness of the derived control law. Introduction It is inevitable that the satellite components is in trouble, so it is one of the hot spots in the research of attitude control to design the control algorithm to achieve the fault tolerant control. A spacecraft attitude compensation controller is designed using adaptive control method in literature [13]. In literature [14], a fault tolerant attitude control strategy is proposed for the non singular terminal sliding mode control method. In literature [9], a passive fault tolerant controller is designed based on time delay method. The attitude tracking control can be realized in the case of 4 flywheels, but the controller must obtain the fault information of the actuators. Application of two stage Kalman filtering algorithm in literature [11]. The Backstepping control method has many advantages such as the decomposition of the complex nonlinear system into many subsystems and the simple design procedure of the controller. Therefore the backstepping can be used to design the attitude controller. Considering the problem of actuator failure, external disturbance and actuator control input constraint in this paper, a method of attitude stabilization control is proposed to achieve high precision and high stability attitude stabilization control. Mathematical Model of the Satellite For description method using Euler angles of satellite attitude exists the singular problems, this paper adopts MRPs describe the satellite attitude, and then the rigid satellite attitude mathematical model can be described by: ( ) ( ) 3 1 1 2 2 4 I F σ σ σ σ σ σ ω σ ω Τ × Τ   = − + +   = ɺ

A novel hybrid method for analog circuit fault classification

Due to the growth prospect of analog circuit fault diagnosis, this paper tends to introduce a novel arithmetic model based on least squares support vector machine (LSSVM) and the semi-supervised learning (SSL) scheme which is adept at cost-saving. The proposed method contains two steps. Firstly, the fact that large deviation may emerge as a result of the empirical risk inspires the idea of an improved transductive least square support vector machine (T-LSSVM) which aims at obtaining the best hyperplane that equipped with the maximum margin to the support vectors no matter whether the samples are labeled or unlabeled. Secondly, to overcome the drawback of typical T-LSSVM, i.e., sensitivity to local minima, a laplcian-transductive least squares support vector machine (Lap-T-LSSVM) is proposed which can perform the fault diagnosis via a laplcian. The experiment adopts band-pass filter circuit as diagnosis object. Simulation results verify that the proposed method is superior to previous SVM in accuracy.

Adaptive neural control of nonstrict system with output constriant

This paper focuses on adaptive neural control for nonlinear system in nonstrict feedback form in the presence of output constraint. Since the backstepping control can not be directly employed to nonstrict feedback structure during controller design. Using the variable separation method, the above obstacle has been overcome. Then, by utilizing barrier Lyapunov function, the issue of output constraint is handled. Combing neural networks (NNs) with the adaptive backstepping technique, it is not only guaranteed that all variables remain bounded in the closed-loop system, but the tracking error is made around the zero with an adjustable small neighborhood. A numerical simulation is provided to demonstrate the control scheme.

A attitude control method for spacecraft considering actuator constraint and dynamics based backstepping

A nonlinear control approach for satellite attitude stabilization maneuver is presented. The controller is developed by using backstepping control technique. The non-ideal dynamical behavior of actuators, referred to as actuator dynamics, is investigated. The satellite s attitude is described by MRPs. The satellites dynamic model can be deduced by a general model of actuator dynamics. And this general model actuator can be expressed all actuators possibly for space application. External disturbances and actuator constraints are all considered during this simulation. Simulation results revealed the control validity of the proposed controller.