Sliding Mode Observer Approach Research Articles

Advanced control strategy for magnetic levitation system: a higher order sliding mode observer approach

Advanced control strategy for magnetic levitation system: a higher order sliding mode observer approach

Fault detection and identification for rolling mill main drive system based on integrated observer under iterative learning strategy

In this article, the problem of multiple fault detection, isolation and reconfiguration of the rolling mill main drive system containing external disturbances is investigated. Considering the nonlinear frictional damping between the rolls and the rolled parts, a nonlinear mathematical model of the main drive system of the mill is established. A comprehensive fault diagnosis scheme based on observer is addressed for this system subjected to unknown external interference. The proposed scheme is divided into two parts. In the first stage, a set of sliding mode observers is designed for system fault detection, and a fault isolation criterion is proposed based on observer redundancy and generalised residual set theory to reveal the fault source. In the second stage, combined with the iterative learning algorithm, an iterative learning-unknown input observer is constructed to realise the accurate estimation of the fault signal. Unlike the existing fault estimation methods, the iterative learning-unknown input observer designed in this article uses the state estimation error of the previous iteration to estimate the fault signal in the current iteration period. Using [Formula: see text] synthesis to design observers for the system will guarantee fault diagnosis robustness. The Lyapunov theory and linear matrix inequality are introduced to prove the convergence of the proposed observer. The simulation study of a 1780-mm hot strip mill evaluates the proposed scheme. Simulation results demonstrate that the sliding mode observer approach can detect faults in the main drive system and isolate faults accurately. In contrast, the iterative learning-unknown input observer method has the lowest fault reconfiguration error (99.87% smaller than the extended state observer, 99.77% smaller than the unknown input observer) and achieves accurate fault signal tracking.

A sliding mode observer approach to oscillatory fault detection in commercial aircraft

The Flight Control System (FCS) is one of the most important systems in all modern aircraft. For such systems it is required to have robust Fault Detection Isolation and Reconfiguration (FDIR) functionalities with high detection performance. In this work we specifically consider the Oscillatory Failure Cases (OFC), which, if not mitigated, can cause additional structural loads for which the aircraft is not designed. A Sliding Mode Observer (SMO) based detection method is proposed for fast and consistent detection of these OFC faults. A benchmark of a generic aircraft FCS equipped with OFC simulation capabilities, as well as the presented solution for detection, have previously been presented within a competition at the 2020 IFAC World Congress.

Descriptor sliding mode observer based fault tolerant control for nuclear power plant with actuator and sensor faults

In sophisticated and complex system such as nuclear power plant, fault estimation and fault tolerant control always play an important role in maintaining the system stability and assuring satisfactory and safe operation. Thus, in this work a fault estimation and fault tolerant control scheme based on sliding mode theory is proposed for a pressurized water reactor type nuclear power plant considering simultaneous actuator and sensor faults. First, using descriptor sliding mode observer approach, an accurate estimation of the system states and sensor fault vector have been obtained simultaneously. Then, based on the estimated information, an integral type sliding mode control scheme is proposed to stabilize the resulting faulty system. With the help of Lyapunov stability theory, reachabilities of the proposed sliding mode surfaces are shown in both the state estimation space and the error estimation space, simultaneously. Finally, the efficacy of the proposed control scheme is shown by applying it to a nuclear power plant.

Sliding Mode Observer-Based Fault Detection in Continuous Time Linear Switched Systems

This paper studies the problem of fault detection for continuous time linear switched systems in the presence of disturbance. For this purpose, a fault detection sliding mode observer approach is designed to generate the residual signal. To minimize the effect of disturbance from the residual, the problem is formulated into H∞ filtering technique to increase more robustness. To deal with the issue of the switched systems stability, the Lyapunov-Krasovskii functional method is utilized along with average dwell time, and linear matrix inequalities are formulated to derive the sufficient conditions. The residual signal is evaluated, and an adaptive threshold is computed for both modes of the switched system. Finally, a simulation example for a case study of boost converter and a numerical example with both abrupt and incipient faults are illustrated to prove the efficacy of the proposed method.

Distributed fault detection and estimation in cyber–physical systems subject to actuator faults

The fault detection and estimation problems for the physical layer network in the cyber-physical systems with unknown external disturbances are investigated in this study. Both bias fault and loss of efficiency scenarios are considered for the actuators. Based on the adaptive threshold method and sliding mode observer approach, a distributed fault detection observer (DFDO) is constructed for each physical layer node to detect the occurrence of actuator faults. Then a relative global estimation error system is defined for the distributed fault estimation observer (DFEO). Compared with the existing results, the proposed DFEO can provide the estimation for not only the actuator bias faults but also the actuators’ efficiency factors under the impact of exogenous disturbance with two gain dynamic update processes. Finally, the feasibility and effectiveness of the given DFDO and the DFEO are examined by Lyapunov stability method and the simulation results.

Fault tolerant sliding mode control for T-S fuzzy stochastic time-delay system via a novel sliding mode observer approach

ABSTRACTIn this paper, a fault estimation and fault-tolerant control problem for a class of T-S fuzzy stochastic time-delay systems with actuator and sensor faults is investigated. A novel sliding mode observer is proposed, which can simultaneously estimate the system states, actuator and sensor faults with good accuracy. Based on the state and actuator fault estimation, a new sliding mode control scheme is developed, which can effectively eliminate the influence of actuator fault. Sufficient conditions for the existence of the proposed observer and fault-tolerant sliding mode controller are provided in terms of linear matrix inequality, and moreover, the reachability of the sliding mode surface can be guaranteed under the proposed control scheme. The propose sliding mode observer and fault-tolerant sliding mode controller can overcome the restrictive assumption that the input matrix of all local modes is the same. Finally, a numerical example is provided to verify the effectiveness of the proposed sliding mode observer and fault-tolerant sliding mode control technique.

Coupled disturbance reconstruction by sliding mode observer approach for nonlinear system

This paper concentrates on the estimation of system states and the reconstruction of disturbances in a class of nonlinear systems considering stateless situation. The disturbances are coupled with time-varying parameters. The sliding mode observer approach is utilized to solve these two issues. Firstly, a descriptor model is presented by transforming the coupled disturbances into the decoupled form. Secondly, the sliding mode observer is designed to estimate the decoupled disturbances and system states of nonlinear systems. The coupled disturbance can be reconstructed hereafter. The detailed methods of designing the observer, together with the sufficient condition to guarantee the existence of the observer are also given. Finally, a simulation and a robot manipulator experiment are provided to examine the validity of the proposed design approach.

Fault‐tolerant control for descriptor stochastic systems with extended sliding mode observer approach

This study concentrates on the fault-tolerant control and fault estimation problems for a class of descriptor stochastic systems with state-dependent faults. A new extended observer method is presented to solve these design problems. First, the descriptor stochastic system is transformed into a non-singular system, and an augmented system is constructed by assembling the fault states into the augmented vector. Then, a novel sliding mode observer with two discontinuous input terms is designed to estimate the states and faults of system. A state-feedback control scheme based on the state estimates is synthesised to guarantee the closed-loop systems stable. Finally, a numerical example is presented to show the effectiveness of the proposed design approach.

Sensor fault-tolerant observer applied in UAV anti-skid braking control under control input constraint

This paper proposes a method for addressing the problem of sensor fault-tolerant control (FTC) for anti-skid braking systems (ABSs). When the wheel velocity sensor of the ABS for unmanned aerial vehicles (UAVs) becomes faulty, wheel velocity failure and feedback instability may occur. Firstly, a fault diagnosis and isolation (FDI) method based on a sliding mode observer approach is introduced to detect and isolate the fault of the sensor. When the wheel velocity sensor is in healthy conditions, the observer works in a diagnosis mode. If faults occur in the sensor, it acts as a wheel velocity estimator. Secondly, an FTC strategy, adopting a feedback compensation structure, is designed with input control constraints. In addition, based on the FDI result, a terminal sliding mode (TSM) controller is designed to guarantee that slip-ratio tracks its appropriate reference values in situations where runways change conditions during landing. The control system switches automatically from control using a wheel velocity sensor to sensorless control mode, so the observer-based FTC scheme is established. It is logical that the ABS keeps observed-state and remains stable when the wheel velocity sensor is broken and during external disturbance. Finally, simulation results show the effectiveness of the proposed method.

Descriptor reduced-order sliding mode observers design for switched systems with sensor and actuator faults

This paper investigates the state and fault estimation problem for linear continuous-time switched systems with simultaneous disturbances, sensor and actuator faults, and two types of observer approaches are presented to solve this design issue. The first one is a linear descriptor reduced-order observer, which generates the exact estimation of state and sensor faults together with disturbances by decoupling them from the state vector without any supplementary design. The second one refers to a descriptor sliding mode observer approach, where the state, disturbances, sensor and actuator faults can be reconstructed simultaneously. In the second method, the reachability of sliding surface is not necessary to be investigated, since the actuator faults can be estimated directly without using the equivalent output error injection scheme as in traditional sliding mode observers. Therefore, both developed observer approaches avoid the sliding surface switching problem of traditional sliding mode observers in application to switched systems. Finally, an example is given to demonstrate the effectiveness of the two designed observer methods.

Fault-Tolerant Sliding-Mode-Observer Synthesis of Markovian Jump Systems Using Quantized Measurements

This paper investigates the design problem of sliding mode observer (SMO) using quantized measurements for a class of Markovian jump systems against actuator faults. Such a problem arises in modern networked-based digital systems, where data have to be transmitted and exchanged over a digital communication channel. In this paper, a new descriptor SMO approach using quantized signals is presented, in which a discontinuous input is synthesized to reject actuator faults by an offline static compensation of quantization effects. It is revealed that the lower bound on the density of a logarithmic quantizer is 1/3, under which the quantization effects could be compensated completely by using the SMO approach. Based on the proposed observer method, the asymptotical estimations of state vector and quantization errors can be obtained simultaneously. Finally, an example of a linearized model of an F-404 aircraft engine system is included to show the effectiveness of the presented observer design method.

Heavy vehicle suspension parameters identification and estimation of vertical forces: experimental results

The aim of the present work is to estimate the vertical forces of heavy vehicle and identify the unknown dynamic parameters using sliding mode observer approach. This observation needs a good knowledge of dynamic parameters such as damping coefficient, spring stiffness, etc. In this paper, suspension stiffness and unsprung masses have been identified. Experimental results carried out on an instrumented tractor have been presented in order to show the quality of the state observation, parameters identification and force estimation. These estimation results are then compared to the measured one coming from the sensors installed in the tractor. Many scenarios have been tested. In this paper, the results coming from zigzag test have been shown and commented.

Fault-tolerant control of Markovian jump stochastic systems via the augmented sliding mode observer approach

This paper is concerned with the stabilization problem for a class of Markovian stochastic jump systems against sensor fault, actuator fault and input disturbances simultaneously. In the proposed approach, the original plant is first augmented into a new descriptor system, where the state vector, disturbance vector and fault vector are assembled into the state vector of the new system. Then, a novel augmented sliding mode observer is presented for the augmented system and is utilized to eliminate the effects of sensor faults and disturbances. An observer-based mode-dependent control scheme is developed to stabilize the resulting overall closed-loop jump system. A practical example is given to illustrate the effectiveness of the proposed design methodology.

Parameter estimation methodology for nonlinear systems: Application to induction motor

This paper deals with on-line state and parameter estimation of a reasonably large class of nonlinear continuous-time systems using a step-by-step sliding mode observer approach. The method proposed can also be used for adaptation to parameters that vary with time. The other interesting feature of the method is that it is easily implementable in real-time. The efficiency of this technique is demonstrated via the on-line estimation of the electrical parameters and rotor flux of an induction motor. This application is based on the standard model of the induction motor expressed in rotor coordinates with the stator current and voltage as well as the rotor speed assumed to be measurable. Real-time implementation results are then reported and the ability of the algorithm to rapidly estimate the motor parameters is demonstrated. These results show the robustness of this approach with respect to measurement noise, discretization effects, parameter uncertainties and modeling inaccuracies. Comparisons between the results obtained and those of the classical recursive least square algorithm are also presented. The real-time implementation results show that the proposed algorithm gives better performance than the recursive least square method in terms of the convergence rate and the robustness with respect to measurement noise.

Design and performance analysis of sliding-mode observers for sensorless operation of switched reluctance motors

This paper presents an analytical and experimental evaluation of the sliding-mode observer (SMO) for eliminating position and speed sensors in switched reluctance motor (SRM) drives. Design guidelines are derived for the SMO to guarantee an upper bound on the observer error for all time. An analysis is presented to demonstrate that the SMO also possesses an automatic adaptation property with respect to the intensity of the measurement noise. The SMO approach is shown, in simulations and in experiments, to provide accurate position and speed estimates under various operating conditions. The resolution and reliability of the scheme are shown to be superior to those obtained using standard state observers. The results demonstrate the applicability of the SMO-based sensorless controllers for SRM drives.