Additive fault detection in nonlinear dynamic systems with saturation

This paper describes the effects of input saturation on the performance of a model-based fault detection method based on the input-output parity equation approach. For this purpose, the level control of a chemical reactor has been chosen as the control process to be analyzed, where the saturation of the dynamic process is due to the inflow control valve, and only additive faults have been considered. This study has been carried out in two ways: first by simulation techniques and second on a real industrial system. In the simulated case, the decrease in the fault detectability due to the saturation effects is shown, and some ways of achieving higher fault detectability are explored. The results obtained in the industrial case complement those obtained in the simulated case, and also reveal the existence of a relation between the control strategy used in the process and additive fault detectability, in the sense that increases in fault detectability are obtained due to the use of faster control strategies.     

Fault diagnosis for a class of nonlinear systems via ESO

In this paper, a novel fault detection and identification (FDI) scheme for a class of nonlinear systems is presented. First of all, an augment system is constructed by making the unknown system faults as an extended system state. Then based on the ESO theory, a novel fault diagnosis filter is constructed to diagnose the nonlinear system faults. An extension to a class of nonlinear uncertain systems is then made. An outstanding feature of this scheme is that it can simultaneously detect and identify the shape and magnitude of the system faults in real time without training the network compared with the neural network-based FDI schemes. Finally, simulation examples are given to illustrate the feasibility and effectiveness of the proposed approach.     

Robust unknown input observer based fault detection for high-order multi-agent systems with disturbances

This paper is devoted to fault detection (FD) for high-order multi-agent systems with disturbances. In order to detect the fault occurred in one agent, the unknown input observer (UIO) is constructed in its neighbor. Two cases are considered, if the perfect UI decoupling condition is satisfied, the UI does not affect the residual; if the condition is not satisfied, this paper proposes a method of partitioning the UI into two parts, such that a subset of the UI does not appear in residual dynamics, and the influence of the other UI is constrained. Simulations are given to demonstrate the effectiveness of the proposed method.     

Fault detection and diagnosis for singular stochastic systems via B-spline expansions

This paper deals with the problem of fault detection and diagnosis (FDD) for singular stochastic systems. The outputs of singular stochastic systems are described by probability density functions (PDFs) based on square root B-spline expansions. Then, two non-linear observers are designed for the FDD. The conditions of stability of the correlative error estimation systems are given by using linear matrix inequalities (LMIs). Finally, the simulation results are presented to indicate that the approach can detect faults and estimate the size of faults.     

Finite-time extended dissipative control for fuzzy systems with nonlinear perturbations via sampled-data and quantized controller

This paper investigates the problem of finite-time extended dissipative control for T–S fuzzy time-varying delay systems with nonlinear perturbations via sampled-data and quantized controller. The definition of finite-time bounded mixed extended dissipative of fuzzy systems is first proposed. Based on the constructed Lyapunov–Krasovskii functional(LKF) and Peng–Parks integral inequality, some sufficient conditions are obtained in the form of linear matrix inequalities(LMIs), which are less conservative than other papers. By combining the input delay approach and dynamic quantizer, the sampled-data and quantized controller is designed to guarantee that the T–S fuzzy system is finite-time bounded mixed extended dissipative. Finally, some numerical examples and practical examples are presented to verify the feasibility and effectiveness of the proposed methods.     

Observation and sliding mode observer for nonlinear fractional-order system with unknown input

The main purpose of this paper is twofold. First, the observability and the left invertibility properties and the observable canonical form for nonlinear fractional-order systems are introduced. By using a transformation, we show that these properties can be deduced from an equivalent nonlinear integer-order system. Second, a step by step sliding mode observer for fault detection and estimation in nonlinear fractional-order systems is proposed. Starting with a chained fractional-order integrators form, a step by step first-order sliding mode observer is designed. The finite time convergence of the observer is established by using Lyapunov stability theory. A numerical example is given to illustrate the performance of the proposed approach.     

Robust fault detection for the dynamics of high-speed train with multi-source finite frequency interference

This paper proposes a composite fault detection scheme for the dynamics of high-speed train (HST), using an unknown input observer-like (UIO-like) fault detection filter, in the presence of wind gust and operating noises which are modeled as disturbance generated by exogenous system and unknown multi-source disturbance within finite frequency domain. Using system input and system output measurements, the fault detection filter is designed to generate the needed residual signals. In order to decouple disturbance from residual signals without truncating the influence of faults, this paper proposes a method to partition the disturbance into two parts. One subset of the disturbance does not appear in residual dynamics, and the influence of the other subset is constrained by $H_{\infty }$ performance index in a finite frequency domain. A set of detection subspaces are defined, and every different fault is assigned to its own detection subspace to guarantee the residual signals are diagonally affected promptly by the faults. Simulations are conducted to demonstrate the effectiveness and merits of the proposed method.     

基于碳纤维框架天基目标探测二维跟踪转台结构优化

为满足某星载太阳辐照度光谱仪对太阳的跟踪指向技术要求,设计了一种二维转台系统.本文对该转台进行了结构的拓扑优化设计、有限元仿真及试验验证.首先,通过研究和比较现有的转台方案,确定以基本地平式作为转台的结构形式,选择性能优良的M55J碳纤维复合材料作为转台结构的主要材料,配合TC4镶嵌件来连接部件.根据拓扑优化结果和工程...     

Robust fault detection for nonlinear networked systems with stochastic interval delay characteristics

In this paper, the problem of observer-based robust fault detection (RFD) for nonlinear networked systems with stochastic interval delay is investigated. By employing the information of probabilistic distribution of networked-induced time-varying delay, the observer-based fault detection filter as residual generator and a proposed performance index as objective function, the RFD of nonlinear networked systems is formulated as an optimization problem. The desired fault detection filter is constructed in terms of certain linear matrix inequalities, which depend on not only delay-interval but also delay-interval-occurrence-rate. Especially, the sub-optimal trade-off of strong robustness from residual signal to disturbance and parameter uncertainty, as well as high sensitivity to fault is obtained by a repeated application of a two-objective optimization algorithm. Numerical simulations are given to illustrate the effectiveness of proposed techniques.     

Simultaneous fault detection and control design for switched systems with two quantized signals

The problem of simultaneous fault detection and control design for switched systems with two quantized signals is presented in this paper. Dynamic quantizers are employed, respectively, before the output is passed to fault detector, and before the control input is transmitted to the switched system. Taking the quantized errors into account, the robust performance for this kind of system is given. Furthermore, sufficient conditions for the existence of fault detector/controller are presented in the framework of linear matrix inequalities, and fault detector/controller gains and the supremum of quantizer range are derived by a convex optimized method. Finally, two illustrative examples demonstrate the effectiveness of the proposed method.     

Robust fault detection for switched positive linear systems with time-varying delays

This paper investigates the problem of robust fault detection for a class of switched positive linear systems with time-varying delays. The fault detection filter is used as the residual generator, in which the filter parameters are dependent on the system mode. Attention is focused on designing the positive filter such that, for model uncertainties, unknown inputs and the control inputs, the error between the residual and fault is minimized. The problem of robust fault detection is converted into a positive L₁ filtering problem. Subsequently, by constructing an appropriate multiple co-positive type Lyapunov–Krasovskii functional, as well as using the average dwell time approach, sufficient conditions for the solvability of this problem are established in terms of linear matrix inequalities (LMIs). Two illustrative examples are provided to show the effectiveness and applicability of the proposed results.     

Optimal adaptive interval type-2 fuzzy fractional-order backstepping sliding mode control method for some classes of nonlinear systems

In this research, a novel adaptive interval type-2 fuzzy fractional-order backstepping sliding mode control (AIT2FFOBSMC) method is presented for some classes of nonlinear fully-actuated and under-actuated mechanical systems with uncertainty. The AIT2FFOBSMC method exploits the advantages of backstepping and sliding mode methods to improve the performance of closed-loop control systems by lowering the tracking error and increasing robustness. To mitigate chattering and the tracking error, a fractional sliding surface is designed. In addition to the fractional sliding surface, an adaptive interval type-2 fuzzy compensator is used to estimate the uncertainty and perturbation of the nonlinear system in order to further reduce chattering caused by switching term as well as to enhance the perturbation rejection. In order to achieve an optimal performance, the multi-tracker optimization algorithm (MTOA) is used. Finally, a number of simulations and experimental tests are carried out to examine the performance of the AIT2FFOBSMC method.     

H∞ mode-dependent fault detection filter design for stochastic Markovian jump systems with time-varying delays and parameter uncertainties

This paper deals with the problem of robust _H∞$H_{\infty }$ fault detection for a class of stochastic Markovian jump systems (SMJSs) The aim is to design a linear mode-dependent fault detection filter such that the fault detection system is not only stochastically asymptotically stable in the large, but also satisfies a prescribed _H∞-norm$H_{\infty }\mathrm{-}\mathrm{norm}$ level for all admissible uncertainties. By using Lyapunov stability theory and generalized Itô formula, some novel mode-dependent and delay-dependent sufficient conditions in terms of linear matrix inequality (LMI) are proposed to insure the existence of the desired fault detection filter. A simulation example and an industrial nonisothermal continuous stirred tank reactor (CSTR) system are employed to show the effectiveness of the proposed method.     

Optimal interval type-2 fuzzy fractional order super twisting algorithm: A second order sliding mode controller for fully-actuated and under-actuated nonlinear systems

In this paper, a novel interval type-2 fuzzy fractional order super twisting algorithm (IT2FFOSTA) which is essentially a second order sliding mode controller is presented. The proposed IT2FFOSTA enhances fractional order super twisting algorithm (FOSTA) by taking advantage of an interval type-2 fuzzy fractional order sliding surface (IT2FFOSS) for some classes of fully-actuated and under-actuated nonlinear systems in presence of uncertainty. The FOSTA significantly reduces the amount of chattering and the IT2FFOSS results in decreasing the tracking error, control effort, and chattering level. In order to control under-actuated systems, a hierarchical sliding surface is employed. The multi-tracker optimization algorithm is utilized to adjust the controller’s parameters; this leads to an optimal performance for the IT2FFOSTA. To examine the performance of the IT2FFOSTA, some simulation and experimental tests on three examples of different classes of fully-actuated and under-actuated systems, including ball and plate, inverted pendulum, and ball and beam systems are carried out. The simulation and experimental results demonstrate the superiority of the IT2FFOSTA in reducing the amount of chattering, tracking error, and control effort compared to those of the other control methods.