Sliding Mode Unknown Input Observer Research Articles

Secure state estimation for cyber-physical systems with unknown input sliding mode observer

Secure state estimation for cyber-physical systems with unknown input sliding mode observer

A Novel Cyber-Attack Detection and Mitigation for Coupled Power and Information Networks in Microgrids Using Distributed Sliding Mode Unknown Input Observer

A Novel Cyber-Attack Detection and Mitigation for Coupled Power and Information Networks in Microgrids Using Distributed Sliding Mode Unknown Input Observer

Decentralized attack detection for multi‐area power systems via interconnection‐decoupled sliding mode observer

AbstractThis article deals with the false data injection attack (FDIA) detection problem for multi‐area power systems. Considering the large‐scale characteristic of the multi‐area power systems, a novel decentralized detection scheme is proposed to detect FDIAs. First, an unknown input sliding mode observer (UI‐SMO) is designed to decouple the interconnected terms, meanwhile, a robust term in the UI‐SMO can attenuate the effect of the load variation, by which the obtained residual is only sensitive to local FDIAs. The strict reachability of the sliding surface in the estimate error space is ensured by the robust term with an auxiliary variable, and the stability of the sliding mode dynamics is achieved. Then, a detection logic is delicately designed based on a two‐phase residual threshold. Due to the strong attenuating ability to load variation, the proposed detection scheme shows better detectability than some existing works with only decoupling interconnections. Finally, the theoretical results are backed up by a three‐area power system simulation with comparison between proposed UI‐SMO‐based and traditional UIO‐based detection scheme.

Real-Time Sensor Fault Identification and Remediation for Single-Phase Grid-Connected Converters Using Hybrid Observers With Unknown Input Adaptation

Unexpected faults that occur in the sensors of the single-phase grid-connected converter (SGC) may deteriorate the control performance ofthe grid current and dc-link voltage and pose risks to the connected distributed generation system. This article proposes an unknown input sliding mode observer (UI-SMO) based sensor fault identification and remediation strategy. Therein, an UI-SMO is established that integrates the observations of the grid current and dc-link voltage with the reconstruction of the unknown input (i.e., load condition of the SGC). Such an observer-based analytical redundancy generates the residuals that indicate the abnormalities of the sensors for fault identification. An adaptive fault-tolerant control (AFTC) strategy for the SGC is developed, where an automated control system reconfiguration with unknown input adaptation is seamlessly implemented by substituting the data reported by the faulty sensors with their observed values. Extensive simulation and experimental studies validate the effectiveness of the proposed UI-SMO-based sensor fault identification and AFTC strategy of the SGC.

Asymptotic Estimation of State, Fault and Perturbation for Nonlinear Systems and Its Fault-tolerant Control Application

This paper addresses the challenge of robust simultaneous estimation of state and actuator faults for Lipschitz nonlinear systems with unknown perturbations acting on both the state dynamics and output measurements. The existing methods enhance the estimation robustness by suppressing the perturbations or decoupling them under satisfaction of the matching condition. This work considers a total elimination of the perturbation effects through perturbation reconstruction. An adaptive sliding mode unknown input observer (ASMUIO) is developed to realize simultaneous asymptotic estimation of the state, faults and perturbations. It leverages a descriptor system reformulation of the original system by regarding partial perturbations as virtual state and the rest part as virtual faults. The proposed ASMUIO has feasibility guarantee and is solved via a linear matrix inequality (LMI) setting. Based on the ASMUIO, an adaptive backstepping fault-tolerant control (FTC) is further designed to achieve good tracking performance. The design efficacy is illustrated through comparative simulations of the proposed method against representative methods in the literature.

Fault tolerant control based on continuous twisting algorithms of a 3-DoF helicopter prototype

Fault tolerant controllers, based on the Continuous Twisting Algorithm (CTA), are designed for robust stabilization of a three-degree-of-freedom (3-DoF) helicopter prototype. Voltage variations (faults) in the actuators are detected and isolated by means of residual-based equations and exploiting the third-order sliding mode differentiator (SMD). Proposed fault detection and isolation (FDI) scheme is tested with intermittent and persistent faults induced by software. A unknown-input sliding mode observer (SMO) is developed to compare and highlight the performance of the proposed FDI-SMD respect to the classic FDI-SMO. Finally, simulations and real-time experiments confirm that CTA-based controllers counteract additive faults. Filtering the signals from residual equations is suggested in order to mitigate the effects of noises and neglected (parasitic) dynamics on the detectors.

Asymptotic estimation of state and faults for linear systems with unknown perturbations

It is challenging to achieve asymptotic estimation of state and actuator faults for systems with unknown perturbations in both the state dynamics and output measurements. To address this, an adaptive sliding mode unknown input observer (ASMUIO) is developed under a mild rank condition of the perturbation distribution matrices. The key idea is to estimate the perturbations simultaneously with the state and faults, which then vanishes the perturbation effects from the estimation error dynamics. Existence conditions and rigorous feasibility proof of the proposed ASMUIO are given. A simulation example is provided to demonstrate the design efficacy in comparison with existing approaches.

Nonlinear unknown input sliding mode observer based chaotic system synchronization and message recovery scheme with uncertainty

In the present manuscript, observer based synchronization and message recovery scheme is discussed for a system with uncertainties. LMI conditions are analytically derived solution of which gives the observer design matrices. Earlier approaches have used adaptive laws to address the uncertainties, however in present work, decoupling approach is used to make observer robust against uncertainties. The methodology requires upper bounds on nonlinearity and the message signal and estimates for these bounds are generated adaptively. Thus no information about the nature of nonlinearity and associated Lipschitz constant is needed in proposed approach. Message signal is recovered using equivalent output injection which is a low pass filtered equivalent of the discontinuous effort required to maintain the sliding motion. Finally, the efficacy of proposed Nonlinear Unknown Input Sliding Mode Observer (NUISMO) for chaotic communication is verified by conducting simulation studies on two chaotic systems i.e. third order Chua circuit and Rossler system.

Real‐Time Sliding Mode Observer Scheme for Shear Force Estimation in a Transverse Dynamic Force Microscope

AbstractThis paper describes a sliding mode observer scheme for estimation of the shear force affecting the cantilever in a Transverse Dynamic Force Microscope (TDFM). The vertically oriented cantilever is oscillated in the proximity to the specimen under investigation. The amplitude of oscillation of the cantilever tip is affected by these shear forces. They are created by the ordered‐water layer above the specimen. The oscillation amplitude is therefore a measure of distance between the tip and the surface of the specimen. Consequently, the estimation of the shear forces provides useful information about the specimen characteristics. For estimating the shear forces, an approximate finite dimensional model of the cantilever is created using the method of lines. This model is subsequently reduced in terms of its order. An unknown input sliding mode observer has been used to reconstruct the unknown shear forces using only tip position measurements and the cantilever excitation. This paper describes the development of the sliding mode scheme and presents experimental results from the TDFM set up at the Centre for Nanoscience and Quantum Information (NSQI) at Bristol University.

Fuzzy robust fault estimation scheme for a class of nonlinear systems based on an unknown input sliding mode observer

In this study, a novel fuzzy robust fault estimation scheme is developed for a class of nonlinear systems when both fault and disturbance are considered. The proposed scheme includes component fault with a nonlinear distribution matrix; as a result, the Takagi–Sugeno model is used to create multiple models. While the Takagi–Sugeno model is used for only the nonlinear distribution matrix of the fault signal, a larger category of nonlinear systems will be considered. This paper presents the problem of robust fault estimation based on fuzzy nonlinear observers, the first one is a fuzzy unknown input observer and the other one is a fuzzy sliding mode observer. The approach decoupled the faulty subsystem from the rest of the system through a series of transformations. Then, the objective is to design a fuzzy unknown input observer guaranteeing the asymptotic stability of the error dynamic using the Lyapunov method and completely removing disturbances; meanwhile, a fuzzy sliding mode observer is designed for a faulty subsystem to generate an estimation of fault based on a quadratic Lyapunov function and some matrices inequality convexification techniques. The sliding motion affects only the faulty subsystem through a novel reduced order fuzzy sliding mode observer; meanwhile, all disturbances are completely removed by fuzzy unknown input observer. Sufficient conditions are established in order to guarantee the convergence of the state estimation error and the results are formulated in the form of linear matrix inequalities. Thus, an exact fault estimator is determined on the basis of linear matrix inequality conditions while the estimation fault is completely insensitive to the disturbance. Finally, a simulation study on an electromagnetic suspension system is presented to demonstrate the g performance of the results compared with a pure sliding mode observer.

H ∞ and Sliding Mode Observers for Linear Time-Invariant Fractional-Order Dynamic Systems With Initial Memory Effect

The H∞ and sliding mode observers are important in integer-order dynamic systems. However, these observers are not well explored in the field of fractional-order dynamic systems. In this paper, the H∞ filter and the fractional-order sliding mode unknown input observer are developed to estimate state of the linear time-invariant fractional-order dynamic systems with consideration of proper initial memory effect. As the first result, the fractional-order H∞ filter is introduced, and it is shown that the gain from the noise to the estimation error is bounded in the sense of the H∞ norm. Based on the extended bounded real lemma, the H∞ filter design is formulated in a linear matrix inequality form, and it will be seen that numerical methods to solve convex optimization problems are feasible in fractional-order systems (FOSs). As the second result of this paper, not only state but also unknown input disturbance are estimated by fractional-order sliding-mode unknown input observer, simultaneously. In this paper, it is shown that the design and stability analysis of the two estimation techniques are not related with the initial history. Through two numerical examples, the performance of the fractional-order H∞ filter and the fractional-order sliding-mode observer is illustrated with consideration of the initialization functions.

Steering vehicle control and road bank angle estimation: application for diagnosis of vehicle limits in bend

This paper deals with the diagnosis of the critical driving situations. This work is divided into three parts: the first one presents two steering controllers using the sliding mode and the switched H∞ controllers, the second one describes an unknown input sliding mode observer, while the last one presents an approach to the diagnosis of critical driving situations. All existence conditions are established using the Lyapunov approach. Simulations are conducted to highlight the efficiency of the proposed approach using the experimental data recorded by an instrumented Peugeot 307 laboratory car. The diagnosis of the critical driving situations is achieved by the speed extrapolation concept using simultaneously a non–linear model, a steering control and road bank observer. The speed extrapolation concept is used in order to evaluate situations under high dynamic loads on a bend, using stability of the sideslip motion.

Time-Delayed Output Feedback Bilateral Teleoperation With Force Estimation for $n$-DOF Nonlinear Manipulators

This brief presents a novel bilateral teleoperation algorithm for <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex Notation="TeX">$n$</tex></formula> degree of freedom nonlinear manipulators connected through time delays. Central to this approach is the use of second-order sliding mode unknown input observers for estimating the external forces, removing the need for both velocity and force sensors. This leads to a lower-cost hardware setup that provides all of the advantages of a position-force teleoperation algorithm. Stability is guaranteed considering the presence of time delays. Numerical and experimental results are presented.

Chaotic synchronisation and secure communication via sliding-mode and impulsive observers

This paper addresses the design of a secure data transmission based on the synchronisation of two chaotic systems, with the use of unknown-input observers. The approach proposed here enhances the security level against intruders thanks to an intricate encryption system. It is shown also that this approach provides more robustness with respect to channel noise. The main feature consists in separating the encryption and synchronisation operations by using two coupled continuous chaotic systems in the transmitter. Technically, the scheme is based on impulsive and sliding mode unknown-input observers. This offers the advantage of estimating the (master) states and of reconstructing the unknown inputs simultaneously. The performances of the proposed method are highlighted by simulation results.

The Combination of High-Gain Sliding Mode Observers Used as Receivers in Secure Communication

This paper considers chaos synchronization and chaos-based secure communication problems based on high-gain sliding mode unknown input observers when the observer matching condition is not satisfied to the drive signal. An auxiliary drive signal vector which satisfies the observer matching condition is introduced and an adaptive and robust observer is developed by using the auxiliary drive signal directly to not only estimate the states but also adjust adaptively the unknown parameters and the Lipschitz constants of the nonlinear terms. A high-gain sliding mode observer is considered to exactly estimate both the auxiliary drive signals and their derivatives in a finite time only based on the original drive signal. The combination of the adaptive and robust observer and the high-gain sliding mode observer becomes the receiver in chaos-based secure communication discussion. A kind of information signal recovering method is developed based on both the state synchronization and exact estimates of the derivatives of the auxiliary drive signals. Finally, a numerical simulation example is given to illustrate the effectiveness of the proposed methods.

Design and experimental validation of linear and nonlinear vehicle steering control strategies

This paper proposes the design of three control laws dedicated to vehicle steering control, two based on robust linear control strategies and one based on nonlinear control strategies, and presents a comparison between them. The two robust linear control laws (indirect and direct methods) are built around M linear bicycle models, each of these control laws is composed of two M proportional integral derivative (PID) controllers: one M PID controller to control the lateral deviation and the other M PID controller to control the vehicle yaw angle. The indirect control law method is designed using an oscillation method and a nonlinear optimisation subject to H ∞ constraint. The direct control law method is designed using a linear matrix inequality optimisation in order to achieve H ∞ performances. The nonlinear control method used for the correction of the lateral deviation is based on a continuous first-order sliding-mode controller. The different methods are designed using a linear bicycle vehicle model with variant parameters, but the aim is to simulate the nonlinear vehicle behaviour under high dynamic demands with a four-wheel vehicle model. These steering vehicle controls are validated experimentally using the data acquired using a laboratory vehicle, Peugeot 307, developed by National Institute for Transport and Safety Research – Department of Accident Mechanism Analysis Laboratory's (INRETS-MA) and their performance results are compared. Moreover, an unknown input sliding-mode observer is introduced to estimate the road bank angle.

Drive Line Control for Electrically Driven Vehicles Using Generalized Second Order Sliding Modes

The drive shaft torque of an electrically driven vehicle is controlled using a generalized second order sliding mode algorithm. Due to the absence of torque sensors the shaft torque is estimated by means of a higher order unknown input sliding mode observer. The observability of the linear drive line model is analyzed by means of observability measures for two different sensor configurations. Based on these results the observer is designed using a reduced sensor set. The control concept is evaluated with a multi body simulation model of an electrically driven rear axle of a hybrid prototype vehicle with unknown backlash in the drive line.

Steering control and road bank angle estimation to evaluate the vehicle behaviour under high dynamic loads: Experimental evaluation

AbstractDriving safely can be ensured by a better understanding of the risk and critical situations. This can be achieved by a good knowledge of road attributes and vehicle dynamic behaviors. This paper proposes two algorithms: the first one is dedicated to a new estimation process which was designed to estimate the vehicle roll and road bank angles, in order to make the road trajectory more realistic. This estimator is based on an unknown input sliding mode observer and a LPV model. The second concerns a robust LPV state output feedback control designed via LMI optimization and gain-scheduling method. The steering control strategy is designed to simulate the non linear four wheel vehicle model under higher dynamic demands. The steering vehicle control and the observer developed here have been validated experimentally using the data acquired on the laboratory vehicle Peugeot 307 developed by INRETS-MA. These algorithms were developed for an application known as “Itinerary Rupture Diagnosis”: to evaluate the physical limits of a vehicle negotiating a bend.

Adaptive sliding mode control of a piezo-actuated bilateral teleoperated micromanipulation system

Abstract Piezoelectric actuators are widely used in micro manipulation applications. However, hysteresis nonlinearity limits the accuracy of these actuators. This paper presents a novel approach for utilizing a piezoelectric nano-stage as the slave manipulator of a teleoperation system based on a sliding mode controller. The Prandtl–Ishlinskii (PI) model is used to model actuator hysteresis in feedforward scheme to cancel out this nonlinearity. The presented approach requires full state and force measurements at both the master and slave sides. Such a system is costly and also difficult to implement. Therefore, sliding mode unknown input observer (UIO) is proposed for full state and force estimations. Furthermore, the effects of uncertainties in the constant parameters on the estimated external forces should be eliminated. So, a robust adaptive controller is proposed and its stability is guaranteed through the Lyapunov criterion. Performance of the proposed control architecture is verified through experiments.

Embedded unknown input sliding mode observer to estimate the vehicle roll and road bank angles: Experimental evaluation

Driving safely can be achieved by better understanding critical situations. This can be achieved by a good knowledge of road attributes and vehicle dynamic parameters. Road bank angle has an important role on the vehicle lateral dynamic; unfortunately, this parameter is not measured by low cost embedded sensor. This paper presents a new estimation process which was designed to estimate the lateral wind force, the road bank and vehicle roll angles using an unknown input sliding mode observer and a linear vehicle model with variant parameters. The vehicle model used here is relatively simple, but it offers a sufficient approximation of the lateral dynamics of the vehicle in normal driving situations. This observer uses the sensor measurements such as the steering angle, the vehicle sideslip angle, the roll rate and the yaw rate. Experimental evaluation proves that the estimation scheme is giving appropriate estimation of the vehicle roll and road bank angles. These tests are carried out using the data acquired on the laboratory vehicle Peugeot 307 developed by INRETS-MA.