Unknown Input Observer

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An Unknown Input Observer for Fault Detection Based on Sliding Mode Observer in Electrical Steering Assist Systems

An Unknown Input Observer for Fault Detection Based on Sliding Mode Observer in Electrical Steering Assist Systems

Steering assist system controls the force transfer behavior of the steering system and improves the steering probability of the vehicle. Moreover, it is an interface between the diver and vehicle. Fault detection in electrical assisted steering systems is a challenging problem due to frequently use of these systems. This paper addresses the fault detection and reconstruction in automotive electrical steering assist systems. Two types of faults including sensor fault and actuator fault are investigated. In this paper, four different model- based fault detection methods including Luenberger observer method, Parity space method, decoupling filter of fault from disturbance method and the unknown input observer are studied. In each method, a sensor and actuator fault is investigated based on the model of the system. Moreover, we examine a method for the fault reconstruction based on the sliding mode observer. Finally, these methods are applied to an automotive electrical steering assist system. The results are presented and thoroughly discussed.
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A proposed method to controller parameter 
		soft tuning as accommodation FTC after unknown input observer FDI

A proposed method to controller parameter soft tuning as accommodation FTC after unknown input observer FDI

The problem of Fault Tolerant Control (FTC) by the use of methods of fault accommodation and reconfiguration is one of the most updated and versatile problems of modern science in control systems engineering. Occurrence of a fault in every components of a system (actuators, sensors, and internal structure) can remove the control loop from the desired state or even destabilize it. The purpose of the fault tolerant control by the accommodation method is to present operational solutions, by the use of which the control loop stability can be maintained and an acceptable performance is obtained (probably weaker than the no-fault condition) in fault occurrence conditions without the need to shut down the system. In this paper, the fault detection and isolation (FDI) issue has been investigated including the fault of system actuators. Design of a fault detection system for a multi-input multi-output (MIMO) system has been done by the method of Unknown Input Observer (UIO). In this method, the system is divided into several sub-systems in a way that the effects of other inputs are entered into states equations as a disturbance. The design method of the observer is such that the disturbance effect is attenuated and only the fault related to a particular input is detected. Having detected and isolated a fault, controlling coefficients are iteratively updated and modified using an auto-tuning method and the closed loop system stability is ensured in the presence of the method. In addition, in order to reduce the oscillation resulting from exerting momentary changes in controlling coefficient, a modification method known as the Sigma modification has been used. Next, the method is implemented on the favorite model of three tanks and the results confirm capability of the designed fault detection system and quality of auto-tuning of the controller.
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Multi-sensor Fault Detection and Isolation for EMB SystemBased on Unknown Input Observer

Multi-sensor Fault Detection and Isolation for EMB SystemBased on Unknown Input Observer

ABSTRACT: Electro-mechanical brake (EMB) systems generate the braking force with electric motors and use several sensors for feedback control. This paper presents a model-based sensor fault diagnostic approach that employs an Unknown Input Observer (UIO) technique to classify sensors as being healthy or unhealthy and even simultaneously occurred faults in two different sensors. The proposed scheme is organized by UIO logic and a decision-making unit. UIO logic estimates sensor values using the inputs and outputs of EMB system and a decision-making unit identifies the faulty sensor based on a deterministic rule and the estimated ones from UIO logic. Unlike other model-based fault detection and isolation schemes, the proposed one needs only one UIO instead of a bank of observers and UIOI is sufficient for detecting and isolating faults simultaneously occurred. Simulation results are presented to verify the effectiveness of this proposed diagnostic approach.
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A decoupling approach to integrated fault-tolerant control for linear systems with unmatched non-differentiable faults

A decoupling approach to integrated fault-tolerant control for linear systems with unmatched non-differentiable faults

This paper proposes a decoupling approach to the integrated design of fault estimation (FE) and fault-tolerant control (FTC) for linear systems in the presence of unknown bounded actuator faults and perturbations. An adaptive sliding mode augmented state unknown input observer is developed to estimate the system state, actuator faults and perturbations, based on a descriptor augmentation strategy and the equivalent output injection concept. Subsequently, an adaptive backstepping FTC controller is designed to compensate the effects of the faults and perturbations acting on the system to ensure robust output tracking. In the proposed observer the effects of the control system perturbations are estimated and the fault effects are compensated to ensure that the FE function is decoupled from the FTC system. This leads to satisfaction of the Separation Principle under the framework of integrated design. When compared with the existing H ∞ optimization single-step integrated FE/FTC design
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Unknown Input Estimation Using Full Order Observer in the Domain of Generalized Matrix Inverse

Unknown Input Estimation Using Full Order Observer in the Domain of Generalized Matrix Inverse

Unknown input estimation has a special importance in many industrial applications like fault detection and identification, cryptography or parameter identifiability, track seeking, railway signaling etc. Several researchers have designed different observers that have been extended to develop UIO and to estimate unknown input. D. G. Luenberger first designed an observer in 1971 which approximately reconstructed missing state variable information [3]. Prof. Das and Prof. T. K. Ghoshal jointly proposed the method of construction of reduced order observer by using generalized matrix inverse [4]. Now to estimate the unknown input, it is necessary to design an unknown input observer (UIO). In [5], a constructive solution to the problem of designing a reduced order Luenberger observer for linear systems subject to arbitrary unknown inputs has been presented. A direct full-order observer design procedure for a linear system with unknown inputs is presented in [6]. Avijit Banerjee, Partha Pratim Mondal and Prof. Gourhari Das constructed a full order observer using the concept of generalized matrix inverse [10]. Alexander Stotsky and Ilya Kolmanovsky presented a paper on unknown input estimation techniques for automotive applications [11]. Unknown input estimation technique for linear discrete-time systems has been given in [7]. The problem of simultaneous estimation of states and unknown inputs for a class of non linear chaotic systems has been addressed in [12]. Avijit Banerjee and Prof Gourhari das presented a method of estimating the unknown input using reduced order Das and Ghoshal observer [4] in [13]. However, in this paper the full order observer constructed in [10] has been extended for estimation of unknown input.
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Accounting for the Great Depression

Accounting for the Great Depression

Our input-friction theory has a simple deter- ministic economy with financing frictions that lead to distortions in the allocation of inputs across two types of firms. Before firms can produce, both types must borrow to pay for an input, say, labor. Firms of the first type, located in sector 1, are financially constrained in that they must pay a higher price for borrowing than do firms of the second type, located in sector 2. We think of these frictions as capturing the idea that some firms, which can be thought of as small, find borrowing harder than others do. One source of the higher price paid by the financially constrained firms is that moral- hazard problems are more severe for small firms. (While this theory is reminiscent of that of Bernanke and Gertler [1989], the margins that get distorted in our model and in theirs are quite different.)
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Observer-Based Adaptive Fuzzy Sliding Mode Control for Switched Uncertain Nonlinear Systems with Dead-Zone Input

Observer-Based Adaptive Fuzzy Sliding Mode Control for Switched Uncertain Nonlinear Systems with Dead-Zone Input

Fuzzy logic systems (FLS) with appropriate adaptive laws algorithms are used to approximate the unknown nonlinear functions appearing in the structure of the switched system. A FLS consists of four parts: the knowledge base, the fuzzifier, the fuzzy inference engine working on fuzzy rules, and the defuzzifier. The problem of adaptive fuzzy output-feedback control for switched uncertain non-linear systems is investigated in [12, 19]. In [13], Li et al. introduced an adaptive fuzzy output-feedback stabilization controller to treat the problem for a class of switched nonstrict-feedback nonlinear systems.
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Intra-observer and Inter-observer Reliability in Direct

Intra-observer and Inter-observer Reliability in Direct

This study aimed to evaluate the reliability factors, and identify causes of error in direct anthropometry method. After training three beginner anthropometrists and following the instructions of anthropometric standards, 48 body dimensions of 42 male students were measured three times. In other words, the physical dimensions of each subject were measured for 9 times. All participants were wearing uniforms during anthropometry, with bare feet. Differences in values of Repeated Measurement Test were explored using SPSS software version 11. The same software was employed to evaluate, through calculating ICC index, the correlation between anthropometrists. Inter-observer repeated measurement test showed significant difference in the measurements taken in 3, 7 and 1 dimension(s) by the three anthropometrists. The average measurement was significantly different at 16 dimensions; this, however, showed no difference at 32 dimensions. Measurements taken by anthropometrist 1 had ICC values of 0.26 (Min) and 0.99 (Max); these values were 0.48 (Min) and 1.00 (Max) for anthropometrist 2 and 0.23 (Min) and 0.98 (Max) for antropometrist 3. The maximum and minimum values of ICC index in all three anthropometrists were respectively close to and above 0.98, and lower than 0.5. High value of ICC in the measured dimensions indicated high reliability of repeated measurements. The decreasing value of some indexes can be attributed to such factors as random error, poor design of measurements tool (which in turn leads to random error), the long time devoted to measurement process, high number of dimension measured, changes in posture of subjects and deviation from the standard position.
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Observer Based Nonlinear Feedback Controls for Heartbeat ECG Tracking Systems

Observer Based Nonlinear Feedback Controls for Heartbeat ECG Tracking Systems

The analysis and design of observed-based nonlinear control of a heartbeat tracking system is investigated in this paper. Two of Zeeman’s heartbeat models are investigated and modified by adding the control input as a pacemaker, thereby creating the control-affine nonlinear system models that capture the general heartbeat behavior of the human heart. The control objective is to force the output of the heartbeat models to track and generate a synthetic electrocardiogram (ECG) signal based on the actual patient reference data, obtained from the William Beaumont Hospitals, Michigan, and the PhysioNet database. The formulations of the proposed heartbeat tracking control systems consist of two phases: analy- sis and synthesis. In the analysis phase, nonlinear controls based on input-output feedback linearization are considered. This approach simplifies the difficult task of developing nonlinear controls. In the synthesis phase, observer-based con- trols are employed, where the unmeasured state variables are estimated for practical implementations. These observer- based nonlinear feedback control schemes may be used as a control strategy in electronic pacemakers. In addition, they could be used in a software-based approach to generate a synthetic ECG signal to assess the effectiveness of diagnostic ECG signal processing devices.
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The Rumsfeld Effect: The unknown unknown

The Rumsfeld Effect: The unknown unknown

Thus autobiographical statements of the kind used in Experiment 1 also showed very few known unknowns. This failure to find stable unknown items may relate to a phenomenon noted by Gentner and Collins (1981). They showed that we can reliably use the fact that we have no memory of an event to infer that the event did not occur. If asked “Did you ever shake hands with Richard Nixon”, people can confidently know that they did not, simply because they have no recollection of the event, and if it had occurred then it is highly probable that they would remember it. Failure to find traces in autobiographical memory will be taken as evidence that a statement is false, whereas failure to find information about a general knowledge statement does not give any reason to believe that it is false. The implication is that for general knowledge as the level of retrieved relevant information decreases, responses tend to a stable “not sure” response, whereas for autobiographical memories, as the level of relevant information decreases, responses tend to a stable “false” response. The less a person can recall about ever being on a bus when it broke down, the more they will tend to believe that it definitely did not happen. Unlike general knowledge, lack of information about personal experiences will not lead to a known unknown.
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WSN BASED SENSING MODEL FOR SMART CROWD MOVEMENT WITH IDENTIFICATION: AN 
EXTENDED STUDY

WSN BASED SENSING MODEL FOR SMART CROWD MOVEMENT WITH IDENTIFICATION: AN EXTENDED STUDY

In this paper, a design of Sliding Mode Observer (SMO) of a class of biochemical processes is proposed. Indeed, nonlinear observers for the estimation of the substances are presented and the estimation of non- measured states in waste water treatment process is addressed. The proposed observers are very successful in accurately estimating states variables. Specifically, sliding mode observer has been investigated for this class of nonlinear systems. Moreover, they are very easy to implement and to calibrate in order to estimate non measurable state. The sliding mode observer is compared with High Gain Observer (HGO) and Extended Kalman Filter (EKF). The performance of the sliding mode observer is illustrated through numerical simulations. The simulation results for the bioreactor application demonstrate the effectiveness of the proposed observer.
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Observer based Control for Time–varying Delay Systems with Delay dependence

Observer based Control for Time–varying Delay Systems with Delay dependence

The state feedback and observer control problem of a class of time-varying delay systems subject to delayed measurements has been investigated. This problem has been cast into a framework of convex optimization. By constructing a Lyapunov– Krasovskii functional and using a recently developed integral inequality approach, existence conditions for the state feedback and the observer controller have been established. The stability conditions obtained are dependent of the delay values, and are generally less restrictive than those previously presented in the literature. Numerical simulations are given and the results show that the designed observers and controllers are feasible and valid.
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REMOTE ACCESS TO IMPROVE ATM SECURITY BY USING IOT

REMOTE ACCESS TO IMPROVE ATM SECURITY BY USING IOT

Shoulder-surfing – using direct observation techniques, such as looking over someone's shoulder, to get passwords, PINs and other sensitive personal information – is a problem that has been difficult to overcome. When a user enters information using a keyboard, mouse, touch screen or any traditional input device, a malicious observer may be able to acquire the user’s password credentials. We present EyePassword, a system that mitigates the issues of shoulder surfing via a novel approach to user input. With EyePassword, a user enters sensitive input (password, PIN, etc.) by selecting from an on-screen keyboard using onlythe orientation of their pupils (i.e. the position of their gaze on screen), making eavesdropping by a malicious observer largely impractical. We present a number of design choices and discuss their effect on usability and security. We conducted user studies to evaluate the speed, accuracy and user acceptance of our approach. Our results demonstrate that gaze- based password entry requires marginal additional time over using a keyboard, error rates are similar to those of using a keyboard and subjects preferred the gaze-based password entry approach over traditional methods
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Observer-Based Robust Adaptive Fuzzy Control for Uncertain Underactuated Systems with Time Delay and Dead-Zone Input

Observer-Based Robust Adaptive Fuzzy Control for Uncertain Underactuated Systems with Time Delay and Dead-Zone Input

Abstract This paper investigates the observer-based robust adaptive fuzzy control problem for a class of uncertain underactuated systems with time delay and dead-zone input. Within this method, the state observer is developed for estimating the unmeasured states in the underactuated system. The fuzzy logic systems are used to approximate the unknown nonlinear functions, and some adaptive laws are introduced to estimate unknown parameters. The dead-zone input which is one of the significant input constraints often exists in many practical industrial control systems. By employing a Lyapunov-Krasovskii functional, it is verified that the proposed controller ensures that all the signals in the closed-loop system are bounded. Simulation results are illustrated to demonstrate the regulation performance of the system output and state estimation by the proposed control method.
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a) Copy your program Basic_1dof_State_Variable_Model_driver.m to a new file sv1_integral_driver.m, then copy the Simulink file Basic_1dof_State_Variable_Model.mdl

a) Copy your program Basic_1dof_State_Variable_Model_driver.m to a new file sv1_integral_driver.m, then copy the Simulink file Basic_1dof_State_Variable_Model.mdl

d) Now we will try and observe what happens when there is a difference between our model and the real system. Modify the observer subsystem in the model (.mdl) file, so the A matrix in the observer is called AA. Just before theyou run the model file, enter the command AA = A*1.5. You should get results like those in Figure 10.

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A Formalism for Evaluating Analytically the Cross-Correlation Structure of a Firing-Rate Network Model

A Formalism for Evaluating Analytically the Cross-Correlation Structure of a Firing-Rate Network Model

First of all we quantified analytically how the correlation depends dynamically on the external input of the network. This has revealed a number of new and partly coun- terintuitive insights. We have shown that a strong input can make the neurons almost independent, and this reveals a simple mechanism to achieve network decorrelation that adds to those, such as the balance of excitation and inhibition (e.g. [27, 55]) or the use of purely inhibitory feedback (e.g. [56]), that were recently proposed. Moreover, we have shown that it is not possible to obtain a mean-field description à la Sznit- man of the neural network, if the anatomical connections are too sparse or our three sources of variability are correlated. We have also proved that correlation depends not only on the input, but also on the topology of the network and on the correlation struc- ture of the sources of randomness. To conclude, we have shown that for very special values of the parameters, the neurons become almost perfectly correlated even if the sources of randomness are independent. We have called this phenomenon stochastic synchronization, and we stress the fact that the formalism developed in this article is able to prove its existence for a completely generic anatomical connectivity whose eigenvalues satisfy a bland condition.
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Power Optimization and Assessment of Optimization Using VLSI Techniques

Power Optimization and Assessment of Optimization Using VLSI Techniques

make sense to expect to estimate power without some information about the circuit input patterns. This information is usually much more readily available to designers than specific input patterns are. All these techniques use simplified delay models, so that they do not provide the same accuracy as, say, circuit simulation. But they are fast, which is very important because VLSI designers are interested in the power dissipation of large designs. In general, it is not clear that any one approach is best in all cases, but we feel that the second statistical approach (MED) offers a good mix of accuracy, speed, and ease of implementation. It may be that a combination of the different techniques can be used for different circuit blocks. The requirement for lower power systems is adapted by many market segments. There are several approaches to reducing power, and the highest economical is through designing for low power. The problem is further complicated by the need to optimize the design for power at all design phases. In summary, low power design requires a rethinking of the conventional design process, where power concerns are often overridden by performance and area considerations. This presented paper showed coverage of low power design methodologies and techniques for estimating the optimization in power of device circuits and systems.
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Assessment of central corneal thickness and corneal endothelial morphology using ultrasound pachymetry, non-contact specular microscopy, and Confoscan 4 confocal microscopy

Assessment of central corneal thickness and corneal endothelial morphology using ultrasound pachymetry, non-contact specular microscopy, and Confoscan 4 confocal microscopy

vs. SP-2000P, and SP-2000P vs. z-ring CS4, but demon- strate good levels of agreement for observer 1 using USP vs. z-ring CS4. The post hoc power result indicates that the CCT measurements in the current study has only 40% power (i.e. 60% type II error) to detect a difference in the present observed means (USP = 555.11, SP-2000P =535.82, z-ring CS4 = 552.57). This demonstrate that the sample size was too small to test for differences of the CCT measure- ments between the three instruments. The mean ± SD, mean differences, limits of agreement, and p-values of CCT measurements using the three instruments are summarized in Table 3.
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Alfalfa Leaf Curl Virus: an Aphid-Transmitted Geminivirus

Alfalfa Leaf Curl Virus: an Aphid-Transmitted Geminivirus

unknown Aphis craccivora unknown unknown unknown unknown unknown Circulifer haematoceps Circulifer tenellus Circulifer haematoceps Micrutalis malleifera Bemisia tabaci FIG 2 A Genome org[r]

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On the Origin of the Observer

On the Origin of the Observer

According to “Second attention epistemology” research, the common observer in its daily life is only partly aware of how his mind elaboration influences his experience. He experiences world and relations with other humans mostly through his emotions and memories. There is an information gap between perception which happens in senses and experience [9]. When observer is fully merged in Being, which happen when it is one with the Zero {} (empty set) his experience is “free” of any mind interpretation. Awakened observer experiences directly what senses perceive. His experience is “objective” in a sense that there is no “subjective” interpretation of the mind.
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