Observer-based Fault Estimation Research Articles

Sliding mode observer-based fault diagnosis and continuous control set fault tolerant control for PMSM with demagnetization fault

A fault detection, estimation and fault tolerant control scheme for demagnetization fault in the permanent magnet synchronous motor systems is proposed in this paper. When demagnetization fault occurs, the system will deviate from the normal state severely. To facilitate the calculation, the demagnetization fault is converted to the dq coordinate system for processing and the resistance change is modeled as the system uncertainty, and the effect of the uncertainty on the system is analyzed. Then a fault detection observer is designed to detect the fault occurrence time, and a sliding mode observer based fault estimation algorithm is designed to estimate the fault and disturbance information. The observer parameters are determined by linear matrix inequality. When the fault information is obtained, a continuous control set fault tolerant control scheme is presented to minimize the impact of fault as far as possible. Finally, experimental results provide evidence of the feasibility of the suggested algorithm.

Learning Observer Based Fault Estimation for a Class of Unmanned Marine Vehicles: The Switched System Approach

Learning Observer Based Fault Estimation for a Class of Unmanned Marine Vehicles: The Switched System Approach

Fault estimation for cyber–physical systems with intermittent measurement transmissions via a hybrid observer approach

This paper investigates the problem of fault estimation for cyber–physical systems (CPSs) with intermittent measurement transmissions. A novel hybrid observer-based fault estimation scheme is proposed to generate estimations of the system state and the fault. Specifically, the correction terms of the designed observer are updated while new output measurements are available. Moreover, the estimation performance of the designed observer is analyzed within a framework of hybrid systems, and sufficient conditions are established to guarantee exponential input-to-state stability with a prescribed convergence rate based on the elaborately constructed Lyapunov function candidate. In contrast to the existing estimation schemes, the requirements of continuous or periodical communication are eliminated, and therefore the proposed one is more applicable for the modern industrial systems integrated with data communication networks. Finally, the application to an aircraft model is presented to illustrate the effectiveness of the developed methods.

Non-fragile sliding mode observer based fault estimation for interval type-2 fuzzy singular fractional order systems

In this paper, an interval type-2 fuzzy model is presented to describe the nonlinear singular fractional order systems (SFOSs) with . The problem of actuator and sensor fault estimation is addressed by designing a non-fragile sliding mode observer (SMO). Firstly, a new criterion is provided to analyse the admissibility of SFOSs, which does not need to divide the fractional order interval into interval and interval to study them separately. Then, by expanding the dimension of the SFOS, the non-fragile SMO and the sliding surface are constructed and the accurate estimations of faults and the SFOS state simultaneously are achieved. A new reaching law is designed, which can divide the process of the system moving to the sliding surface into three stages. Further the control law is constructed to guarantee the observation error reaches the sliding surface in finite time. Finally, three examples show the effectiveness of the proposed scheme.

Adaptive adjustable dimension observer based fault estimation for switched fuzzy systems with unmeasurable premise variables

This paper focuses on the sensor fault estimation problem for a kind of switched nonlinear systems. A novel fault estimation observer design method is proposed, which can reconstruct the sensor fault and system state, simultaneously. T-S fuzzy model is considered to describe the nonlinear dynamics in switched systems, and the premise variables of the fuzzy models are assumed to be dependent on the unmeasurable system state rather than the measurable variables, which leads to that there is a Lipschitz nonlinear term in the error dynamics. The Lipschitz nonlinear term is divided into two parts, and their influence on estimation result is decoupled and canceled by selecting appropriate observer parameter matrices and adding adaptive compensator, respectively. Compared with the existing results, the proposed method does not require the Lipschitz constant information. Thus, it avoids calculating the Lipschitz constant and reduces the conservatism caused by introducing the Lipschitz constant into LMIs. Besides, the order of the designed observer is not fixed, and can be selected in a certain range, which implies that the proposed method is with more design freedom for different conditions. At last, two examples are listed to verify the proposed fault estimation approach.

Multi-controller-based fault tolerant control for systems with actuator and sensor failures: Application to 2-body point absorber wave energy converter

In this paper, both the fault estimation and fault-tolerant control (FTC) issues are investigated for a class of continuous-time dynamic system with actuator and sensor failures. Firstly, an augmented model is developed based on the system state and the sensor failure. Then, under the adaptive law for estimated actuator failure, an adaptive observer-based fault estimator is designed to obtain the estimated state and failures. Moreover, based on the estimated information, an observation state-based multiple-controller is constructed to ensure the asymptotic stability for the faulty closed-loop system with a suitable H∞ performance index. Finally, the effectiveness and applicability of the proposed fault estimation and FTC design strategies are fully verified via a case study with a class of 2-body point absorber wave energy converter with actuator and sensor failures.

Reduced-order intermediate variable observer based fault estimation and fault-tolerant control for fuzzy stochastic systems with exogenous disturbance

This paper studies fault estimation and fault-tolerant control problems for fuzzy systems with exogenous disturbance and stochastic noise. The fuzzy reduced-order intermediate variable observers and the disturbance observers are proposed to reconstruct the sensor fault, the actuator fault and the disturbance. According to the estimated results, the observer based fault-tolerant controllers are devised. Compared with the full-order observer design method, the designed reduced-order observers are with lower dimensions and less cost. Different from the classic intermediate observer, the feedback term of the output estimation error is introduced into our observers, which increases the design freedom. And the obtained linear matrix inequality conditions can ensure that the whole closed-loop systems are mean-square exponentially stable. Finally, two examples are offered to verify the feasibility of the proposed method.

Sensor Fault-Tolerant Control of Microgrid Using Robust Sliding-Mode Observer.

This work investigates sensor fault diagnostics and fault-tolerant control for a voltage source converter based microgrid (model) using a sliding-mode observer. It aims to provide a diagnosis of multiple faults (i.e., magnitude, phase, and harmonics) occurring simultaneously or individually in current/potential transformers. A modified algorithm based on convex optimization is used to determine the gains of the sliding-mode observer, which utilizes the feasibility optimization or trace minimization of a Ricatti equation-based modification of H-Infinity () constrained linear matrix inequalities. The fault and disturbance estimation method is modified and improved with some corrections in previous works. The stability and finite-time reachability of the observers are also presented for the considered faulty and perturbed microgrid system. A proportional-integral (PI) based control is utilized for the conventional regulations required for frequency and voltage sags occurring in a microgrid. However, the same control block features fault-tolerant control (FTC) functionality. It is attained by incorporating a sliding-mode observer to reconstruct the faults of sensors (transformers), which are fed to the control block after correction. Simulation-based analysis is performed by presenting the results of state/output estimation, state/output estimation errors, fault reconstruction, estimated disturbances, and fault-tolerant control performance. Simulations are performed for sinusoidal, constant, linearly increasing, intermittent, sawtooth, and random sort of often occurring sensor faults. However, this paper includes results for the sinusoidal nature voltage/current sensor (transformer) fault and a linearly increasing type of fault, whereas the remaining results are part of the supplementary data file. The comparison analysis is performed in terms of observer gains being estimated by previously used techniques as compared to the proposed modified approach. It also includes the comparison of the voltage-frequency control implemented with and without the incorporation of the used observer based fault estimation and corrections, in the control block. The faults here are considered for voltage/current sensor transformers, but the approach works for a wide range of sensors.

Observer-based fault estimation in steer-by-wire vehicle

In this paper, the mechanism for the fault estimation (FE) problem for a steer-by-wire (SBW) vehicle with sensor and actuator faults is investigated. To deal with the design issues, we transformed the nonlinear model of SBW vehicle into a new coordinate system to jointly estimate the sensor and actuator faults. In the new coordinate system, the Lipschitz conditions and system uncertainties are also considered. The proposed schemes essentially transform the original system into two subsystems, where subsystem-1 includes the effects of actuator faults but is free from sensor faults and subsystem-2 only has sensor faults. Then two sliding mode observers (SMOs) are designed to estimate actuator and sensor faults, respectively. The sufficient conditions for the existence of the proposed observers with FI°o performance are derived and expressed as an LMI optimization problem such that the upper bounds of the state and fault estimation errors can be minimized. Finally, the numerical example with simulation results is provided to validate the practicability and efficacy of the developed estimation strategy

Observer-based fault estimation for a class of discrete-time switched affine systems: An application to the DC-DC converter

This paper studies the observer-based fault estimation for a class of discrete-time switched affine systems. A new class of fault estimator with an affine term is first established based on the state observer approach, and a target solution problem of the augmented error system is established under the H∞ performance scheme. The min-type Lyapunov function and its associated switching function are used to obtain the stability condition of the augmented error system in terms of Lyapunov-Metzler inequality. The idea of minimizing the volume of the ellipsoid is adopted containing the set of attraction in order to obtain an attraction set as small as possible. Through solving an optimization problem, the stability of augmented error system can be ensured, and the corresponding fault estimator design is realized in the form of linear matrix inequalities. Finally, a practical application of three level DC-DC multicellular converter is illustrated to verify the effectiveness and practicability of the developed observer-based fault estimation approach.

Novel neural observer based fault estimation, reconstruction and fault-tolerant control scheme for nonlinear systems

This research is concerned with the adaptive neural network observer based fault approximation and fault-tolerant control of time-varying nonlinear systems. A new strategy for adaptively updating the weights of neural network parameters is proposed to enhance fault detection accuracy. Lyapunov function theory (LFT) is applied for adaptively updating the learning parameters weights of multi-layer neural network (MLNN). The purpose of using adaptive learning rates to update the weight parameters of MLNN is to obtain the global minima for highly nonlinear functions without increasing the computational complexities and costs and increase the efficacy of fault detection. Results of the proposed adaptive MLNN observer are compared with conventional MLNN observer and high gain observer. The effects of various faults or failures are studied in detail. The proposed strategy shows more robustness to disturbances, uncertainties, and unmodelled system dynamics compared to the conventional neural network, high gain observer and other existing techniques in literature. Fault tolerant control (FTC) schemes are also proposed to account for the presence of various faults and failures. Separate sliding mode control (SMC) based FTC schemes are designed for each observer to ensure stability of the faulty system. The suggested strategy is validated on Boeing 747 100/200 aircraft. Results demonstrate the effectiveness of both the proposed adaptive MLNN observer and the FTC based on the proposed adaptive MLNN compared to the conventional MLNN, high gain observer and other existing schemes in literature. Comparison of the performance of all the strategies validates the superiority of the proposed strategy and shows that the FTC based on proposed adaptive MLNN strategy provides better robustness to various situations such as disturbances and uncertainties. It is concluded that the proposed strategy can be integrated into the aircraft for the purpose of fault diagnosis, fault isolation and FTC scheme for increasing the performance of the system.

Adjustable dimension descriptor observer based fault estimation for switched nonlinear systems with partially unknown nonlinear dynamics

This paper focuses on the fault estimation problem for switched systems with partially unknown nonlinear dynamics, actuator and sensor faults, simultaneously. The fault estimation observers are constructed, in which the observer dimension is not fixed and can be selected in a certain range. Both the disturbance decoupling and disturbance attenuation are considered, where the unknown nonlinear dynamics can be decoupled and the effect of modeling error and measurement disturbance is attenuated. Based on the average dwell time and the piecewise Lyapunov function, the observer parameter matrices can be calculated by solving LMIs and matrix equations. Finally, two examples are listed to verify the proposed fault estimation approach.

A new separated fault estimator and fault-tolerant control design strategy for uncertain nonlinear systems using T-S fuzzy modeling

In this paper, a new separated design of adaptive observer-based fault estimator (FE) and fault-tolerant control (FTC) is introduced for nonlinear systems along with sensor and actuator faults in the presence of external disturbance and parametric modeling uncertainty by T-S fuzzy modeling, which can easily challenge integrated design strategies. Firstly, a new fuzzy adaptive FE estimates actuator/sensor faults, and the system states simultaneously and also can automatically estimate and compensates bi-directional uncertainties between FE function and control system. Secondly, a fuzzy state feedback FTC controller is designed based on these estimations. Then the proposed separated FE/FTC design presented which is solved by linear matrix inequality via $H_infty$ optimization. Finally, a tutorial example of an inverted pendulum on a cart demonstrates the validity and effectiveness of the proposed design.

$${L_\infty }$$ Fault Estimation and Fault-Tolerant Control for Nonlinear Systems by T–S Fuzzy Model Method with Local Nonlinear Models

This paper investigates the problems of the observer-based fault estimation (FE) and fault-tolerant control (FTC) for nonlinear systems subjected to external disturbances by the T–S fuzzy model method with local nonlinear models. Firstly, an FE strategy is proposed based on the unknown input observer technology, where the local nonlinear terms can be decoupled from the FE error system for relaxing the design of observer. Then, by using the FE information, a fuzzy fault-tolerant controller is designed to guarantee the stability of the system. Additionally, in the design schemes of the FE observer and the fault-tolerant controller, the $${L_\infty }$$ method is used to deal with the problems of FE and FTC for the system with persistent disturbance such that the robustness of the system against the persistent external disturbance can be increased. Compared with the traditional $${H_\infty }$$ method which is only applicable for dealing with the energy bounded signals, the $${L_\infty }$$ FTC strategy proposed in this paper can deal with the persistent disturbance such that the shortcomings of the traditional $${H_\infty }$$ approach are overcome. Finally, the effectiveness of the proposed method is verified by simulation results.

Adjustable dimension descriptor observer based fault estimation of nonlinear system with unknown input

In this paper, the fault estimation problem is considered for nonlinear system with process fault, sensor fault and unknown input. A novel adjustable dimension augmented descriptor observer is designed. Based on the proposed observer, the system state, process and sensor faults can be estimated simultaneously, and the unknown input can be decoupled from the error dynamic. The observer parameters are calculated by solving LMI and matrix equations. The observer order can be selected in a certain range, which is helpful to achieve the compromise between the estimation cost and accuracy. At last, two simulation examples are listed to show the effectiveness of the proposed approach.

Optimal Observer-Based Fault Detection and Estimation Approaches for T–S Fuzzy Systems

In this article, optimal observer-based fault detection (FD) and estimation schemes for Takagi–Sugeno fuzzy systems with process faults are investigated. In particular, an optimal FD scheme for fuzzy systems is proposed first aiming at enhancing the sensitivity to the faults and simultaneously increasing robustness against unknown inputs, which gives the extension of the socalled unified solution to fuzzy systems. To further provide the fault information, a least squares fault estimation scheme is developed. It is noteworthy that, the observers for the proposed FD and estimation schemes are updated online recursively. A case study on the laboratory three-tank system is then given to demonstrate the proposed FD and estimation approaches.

Robust Fault Estimation Using the Intermediate Observer: Application to the Quadcopter.

In this paper, an actuator fault estimation technique is proposed for quadcopters under uncertainties. In previous studies, matching conditions were required for the observer design, but they were found to be complex for solving linear matrix inequalities (LMIs). To overcome these limitations, in this study, an improved intermediate estimator algorithm was applied to the quadcopter model, which can be used to estimate actuator faults and system states. The system stability was validated using Lyapunov theory. It was shown that system errors are uniformly ultimately bounded. To increase the accuracy of the proposed fault estimation algorithm, a magnitude order balance method was applied. Experiments were verified with four scenarios to show the effectiveness of the proposed algorithm. Two first scenarios were compared to show the effectiveness of the magnitude order balance method. The remaining scenarios were described to test the reliability of the presented method in the presence of multiple actuator faults. Different from previous studies on observer-based fault estimation, this proposal not only can estimate the fault magnitude of the roll, pitch, yaw, and thrust channel, but also can estimate the loss of control effectiveness of each actuator under uncertainties.

A new method of fault estimation and tolerant control for fuzzy systems against time-varying delay

In the study, the issues of observer-based fault estimation (FE) as well as active fault-tolerant control (FTC) are considered based on a series of Takagi–Sugeno (T–S) fuzzy models against time-varying delay. Utilizing these obtained (k−1)th messages, a new k-step T–S fuzzy fast adaptive FE method is suggested to construct this observer. And a full-order controller is suggested to make the closed-loop system stable by compensating this fault effect. In contrast to the existing study works, the addressed controller can be carried out in a wider application scope. A fuzzy Lyapunov–Krasovskii functional method is utilized to analyze the stability of the closed-loop system. Meanwhile, sufficient stability conditions are proposed through linear matrix inequalities (LMIs) calculated by Matlab toolbox. Finally, the merits of this suggested approach are demonstrated via two simulation examples.

Integrated observer based fault estimation for a class of Lipschitz nonlinear systems

SummaryThe fault estimation for a class of nonlinear systems with Lipschitzian nonlinearities and faults is studied in this article. An integrated estimation observer that covers the robust estimation observer (REO) and adaptive estimation observer (AEO) is proposed to improve the accuracy of fault estimation. Compared with the traditional AEO, the designed observer does not involve the output derivatives and can be more suitable for practical applications. Furthermore, based on the designed observer, the coupling term emerging in the obtained error dynamics can be eliminated reasonably and less conservative stability conditions for the error dynamics can be obtained, whereas the case is hard to be achieved based on the existing intermediate estimator approach in the literature. Compared with the traditional REO and AEO, the fault can be estimated with a good accuracy by using the proposed integrated estimation observer. Numerical examples test the effectiveness and advantages of the proposed method.

Integrated fault estimation and fault tolerant control for systems with generalized sector input nonlinearity

This paper presents a Fault Tolerant Control (FTC) scheme for systems with L2-bounded disturbances and generalized sector nonlinearity at the input. An adaptive observer-based fault estimation (FE) scheme is used to estimate the fault. The nonlinearity causes the control input (the measurable controller output, which is injected into the FE scheme) to differ from the actuator output (which enters the plant); this mismatch (together with the disturbances) causes interactions between the FE and FTC schemes, violating the separation principle and hence they cannot be designed separately. We introduce a method that integrates both FE and FTC schemes, and design them simultaneously (thus overcoming the violation of the separation principle), guaranteeing bounded stability. To obtain the sufficient conditions for stability and minimum L2-gain performance for disturbance rejection, we use the Sector Condition (SC) and successfully re-casted the design as Linear Matrix Inequalities (LMIs) which can be performed in a single step and yield tractable solutions. Through a numerical example, we demonstrate the effectiveness of the proposed method.