Observer Design Approach Research Articles

Set‐membership state estimation for delayed switched systems with interval uncertainty: A zonotopic approach

SummaryConsidering the existence of time delay and interval uncertainty, a set‐membership state estimation problem based on zonotopes is studied for discrete‐time switched systems subject to unknown but bounded noises. To conform the actual situation, a state observer asynchronous with the subsystem is designed. The performance is introduced to attenuate the effect of noises in the observer design. By dealing with the interval uncertainty, the design approach of observer is given and transformed into a convex optimization problem which can be solved off‐line. The zonotope and the estimation interval containing state are provided based on the observer. Finally, a numerical example is given to verify the effectiveness of the proposed algorithm.

Distributed finite-time attack detection and estimation of intelligent connected vehicle platoon

ABSTRACT This paper presents a distributed finite-time observer design approach for the problem of intelligent connected vehicles (ICVs) containing both attack signals and unknown disturbances. Firstly, an analysis is conducted on the two types of network attacks that ICVs may encounter, followed by the construction of a dynamic vehicle model and its transformation into a state space equation. Secondly, an intermediate variable is introduced to design a distributed attack estimation observer, which both ensures accurate estimation of the vehicle safety state and attack signal within a limited time and overcomes the constraints of traditional observers. Additionally, sufficient conditions for the finite-time boundedness of the observer error system with H ∞ performance are provided in the form of linear matrix inequalities. Furthermore, an adaptive threshold attack detection method is designed. Finally, the simulation results validate the efficiency of the design methods.

Dynamic output feedback based fault tolerant control for continuous-time switched affine systems via reduced-order observer

In this study, the issue on dynamic output feedback fault-tolerant controller design is addressed for a class of continuous-time switched affine systems in the presence of actuator faults. The existence of affine terms gives rise to the lack of a common equilibrium point and further makes it more difficult to propose the desired output-feedback-based fault-tolerant control scheme. Firstly, the actuator fault estimation is achieved through a reduced-order observer design approach. Then, a kind of dynamic output feedback controller is constructed to perform the fault tolerance goal by utilizing fault estimation information. Moreover, the mode-dependent average dwell time switching constraint is borrowed to avoid the chattering owing to the high-frequency switching. The sufficient conditions with less conservative are derived to guarantee the practical exponential stability of closed-loop system with a prescribed L∞ gain. Finally, both the effectiveness and validity of the designed fault-tolerant control strategy are illustrated via a case study of a buck-boost DC-DC converter.

Sampled-data observer design for Linear Kuramoto–Sivashinsky systems with non-local output

The aim of this paper is to provide a novel systematic methodology for the design of sampled-data observers for Linear Kuramoto–Sivashinsky systems (LKS) with non-local outputs. More precisely, we extend the systematic sampled-data observer design approach which is based on the use of an Inter-Sample output predictor to the class of LKS systems. By using a small-gain methodology we provide sufficient conditions ensuring the Input-to-Output Stability property of the estimation errors in the presence of measurement noise. Our Inter-Sample output predictor contains a tuning term which can enlarge significantly the Maximum Allowable Sampling Period.

Sampled-Data Observer Design for Linear Kuramoto-Sivashinsky Systems with Non-Local Output

The aim of this paper is to provide a novel systematic methodology for the design of sampled-data observers for Linear Kuramoto-Sivashinsky systems (LKS) with non-local outputs. More precisely, we extend the systematic sampled-data observer design approach which is based on the use of an Inter-Sample output predictor to the class of LKS systems. By using a small-gain methodology we provide sufficient conditions ensuring the Input-to-Output Stability property of the estimation errors in the presence of measurement noise. Our Inter-Sample output predictor contains a tuning term which can enlarge significantly the Maximum Allowable Sampling Period.

Describing the scope of practice of patient navigators for older adult patients with complex care needs

Introduction: Transitions in care (e.g., discharge to home) are stressful for patients, especially for older adults living with complex conditions. To bridge the care gap and improve the continuity of care across care transitions, a new model of care was introduced at a large metropolitan hospital in partnership with a community agency that uses patient navigators which are embedded in the hospital’s care teams, including emergency, acute, and rehabilitative care. Patient Navigators are regulated healthcare professionals with experience in care coordination to assist with care planning during a patient's hospital stay, and to support patients/families in their care journey to their home for up to 90 days. There is qualitative evidence demonstrating that patient navigators have increased patient/caregiver satisfaction at the hospital but further evidence is required to characterize the scope of practice of navigators to better understand how they are integrating with the larger clinical team. 
 Aim∕Objectives∕Theories∕Methods: The purpose of this study was to characterize the scope of practice of patient navigators. The objectives were to identify the characteristics of patients who have been supported by a navigator and to determine the reasons for referral and intervention, service length, and post-discharge location. To accomplish this aim, a cohort observational study design approach was used, which included using clinical notes collected by the patient navigator as well as hospital decision-support chart data between November 2019 to November 2021. Frequencies and descriptive statistics were used to analyze the data.
 Highlights∕Results∕Key Findings: Of the 176 cases referred to the patient navigator, 28 were deemed not appropriate for the service, 53 received consults (3 days or less of support), and 90 were assigned to the navigator caseload. Of the 90 on the navigator caseload, the average age was 78.9 (SD=9.9) and 44 had a caregiver present to support them. The top reasons were: 1) service connection to community service; 2) housing related; 3) discharge planning, and 4) provider connection. The average service days was 74 days (Median=49 days). The post-discharge location were: home (66%), rehab/reactivation (15%), palliative/deceased (13%), long-term care (3%), acute care (1%), or unknown (2%).
 Conclusion: To our knowledge, this is the first Canadian study to describe a patient navigator program for older adults with complex care needs in a hospital setting. The finding suggest that patient navigators are playing an active role in helping older adult patients by linking them to appropriate services while also supporting patients and caregivers. The data illustrates that it is a high resource service, with clients receiving supports over a 74 day period, but led to a large proportion of clients being returned back home. Since this is a novel care model, the findings will help provide the evidence needed to make a case for implementing patient navigators.
 Implications: The Patient Navigator played an important role in advocacy liaising with health and social care providers in the community, and a critical role in discharge planning in the hospital providing follow-up support to patients/families while they transitioned back home for up to 90 days.

Design and construction of station caverns – Melbourne Metro Tunnel Project

AbstractThe Metro Tunnel Project in Melbourne, Australia, involves the construction of 9 kms of twin rail tunnels and five new underground stations, including the State Library and Town Hall in the City Centre. The stations aim to provide spacious areas measuring around 260 m in length, 30 m in width, and 23 m in height. To address ground conditions, load behaviour, and land constraints, the stations are being built as trinocular form caverns, with a sequential excavation of the central (cavern) tunnel followed by the outer (platform) tunnels. Advanced 3D numerical analyses guided the design of the primary support and permanent linings, with temporary steel columns incorporated into permanent linings for efficiency. Close collaboration and an observational design approach facilitated efficient construction methods and work sequencing. The paper presents insights into the successful design, construction, and verification approaches on aspects of the project.

Adaptive Neural Network-Based Observer Design for Switched Systems With Quantized Measurements.

This study is concerned with the adaptive neural network (NN) observer design problem for continuous-time switched systems via quantized output signals. A novel NN observer is presented in which the adaptive laws are constructed using quantized measurements. Then, persistent dwell time (PDT) switching is considered in the observer design to describe fast and slow switching in a unified framework. Accurate estimations of state and actuator efficiency factor can be obtained by the proposed observer technique despite actuator degradation. Finally, a simulation example is provided to illustrate the effectiveness of the developed NN observer design approach.

Proportional-Integral Observer Design for Multirate-Networked Systems Under Constrained Bit Rate: An Encoding-Decoding Mechanism.

In this article, the proportional-integral observer design problem is studied for a class of multirate networked systems subject to constrained bit rate. The sensor sampling period is allowed to be different from the system updating period and, to facilitate the observer design, the underlying multirate system is cast into a general single-rate one by resorting to the lifting technique. In order to curb the communication burden and promote the data security, the encoding-decoding procedure is implemented on the sensor-to-observer channel to convert the measurement signals into binary codewords. A sufficient condition is first proposed to reveal the fundamental relationship between the bit-rate constraints and the decoding accuracy, and then the exponentially ultimate boundedness of the error dynamics is assessed with the aid of the Lyapunov method. Subsequently, the desired observer gains are determined by solving two optimization problems with the aim to achieve two distinct performance indices, namely, the smallest ultimate bound and the fastest decay rate. Finally, the validity of the developed observer design approach is thoroughly demonstrated via the simulation examples.

The Relationship between the Quality of Physiotherapy Services and the Level of Satisfaction of Patients with Musculoskeletal Cases Physiotherapy Independent Practice in Malang Raya

Objective: To determine the relationship between the quality of physiotherapy services and the level of patient satisfaction with musculoskeletal cases of independent practice of physiotherapy in Malang Raya. Methods: Observational analytic research design approach cross sectional design. The sample in this study is The sample of this study were patients with musculoskeletal cases who underwent independent practice physiotherapy in Malang Raya and were willing to be part of the sample. Sample technique using convenience sampling with a total sample of 35 people. Data collection tool for service quality using Instruments Servqual and patient satisfaction using the Medrisk Instrument. Test Data analysis was carried out then normality test, correlation test using test pearson rhu in the SPSS program. Results: Based on the results of the significance value correlation test (2-tailed) 0.000 indicates a value <0.05 with information H0 is rejected and H1 is accepted. Pearson Correlation of 0.642**, which is included in the category of strong relationship level. Conclusion: that there is a correlation between the quality of service and the level of patient satisfaction with musculoskeletal cases of independent practice of physiotherapy in Malang Raya.

Frequency Information-Based Observer Design for Takagi–Sugeno Fuzzy Affine Systems

This brief studies the problem of observer design for discrete-time uncertain Takagi-Sugeno (T-S) fuzzy affine systems subject to external disturbances and measurement noises with known frequency ranges. A class of novel observers with more design parameters is proposed. Based on the premise variable space partition information, piecewise Lyapunov functions are constructed together with the frequency range information of disturbances and noises, less conservative asymptotic stability with finite frequency performance analysis results are obtained. Then, based on Projection lemma, a novel observer design approach is proposed to T-S fuzzy affine systems, which tends to be less conservative than the non-frequency information and/or common Lyapunov function based observer design ones. Finally, simulation results on a circuit system are given to demonstrate the effectiveness and advantages of the proposed method.

Indirect Data-Driven Observer Design Using Neural Canonical Observer Structures

An indirect data-driven observer design approach for nonlinear discrete-time systems based on an input-output injection with neural canonical observer structures is proposed. An artificial neural network auto-encoder structure, trained with recorded state, input, and output data, is used for the identification of a system in a nonlinear Brunovsky observer form with output transformation. The neural approximations of the transformations and the input-output injection can be used to construct an observer with linear error dynamics using methods from linear control theory. The approach is demonstrated on two academic examples and on an industrially-motivated problem with a sampled continuous-time model.

Toward a Cooperative ADAS for Train Driving based on Real-Time Human Parameters and Delay Estimation

Modern railway research focuses on autonomous train control systems, however the existing rolling stock still requires human driver in the control loop, especially for safety critical operations. This article is about the interaction of the train driver and an autonomous driver advisory system (ADAS) based on human state estimation to avoid confrontative and encourage integrative cooperation modes. This is made possible using a special observer design approach that allows to estimate driver's reaction delay to ADAS advises, and to reconfigure the ADAS mode accordingly. The result is that the driver acceptance rates (for ADAS suggestions) improve, along with the overall train control performance, ensuring successful mission. Theoretical developments and simulation results are provided.

Observer-based boundary feedback control for attitude tracking of rigid bodies with partially liquid-filled cavities

In the attitude tracking control tasks of rigid bodies with partially filled cavities, liquid sloshing is a crucial characteristic that hinders effective controller design and accuracy improvement. To overcome this problem, we propose a novel boundary feedback control (BFC) scheme based on the PDE-ODE cascade governing the rigid body attitude and internal liquid dynamics. We further develop an innovative PDE-based observer to cope with requirements on the infinite number of unmeasurable boundary states. Thus, using only attitude data, the discussed boundary controller can stabilize the attitude tracking error and the infinite-dimensional internal dynamics. The asymptotic stability of the closed-loop observer-based controller is established via the Lyapunov direct method. Finally, to show its efficacy, the proposed methodology is applied to the attitude tracking problem of a typical liquid-propellant satellite. In summary, the novelty is twofold: (i) due to dealing with the original involved PDE-ODE cascade, the formulated control strategy is more accurate than the relevant studies that have used liquid rigidity and potential ideal flow assumptions; (ii) the observer design approach is much broader than existing ones for nonlinear parabolic-type PDEs.

Unknown Input Functional Observer Design for Discrete-Time Interval Type-2 Takagi–Sugeno Fuzzy Systems

This article proposes a novel unknown input functional observer design approach toward discrete-time interval type-2 Takagi–Sugeno fuzzy system models subject to measurable and unmeasurable premise variables. By constructing a new state vector that contains both the unknown inputs and the system states, functional observers are proposed for the cases with measurable and unmeasurable premise variables to estimate this new state vector for unknown input and/or state estimation. The observer design problem is converted into the solvability issue of a linear matrix equation involving observer gain matrices, and the existence conditions of the observers are explicitly obtained based on matrix rank analysis. Meanwhile, instead of solving the intricate Sylvester equation directly, the solution of the simplified matrix equation is employed to derive the observer gains. Moreover, the effectiveness and the superiority of the presented method are demonstrated via two illustrative examples.

Prevalence Of Low Energy Availability In High Level Kenyan Middle- And Long-distance Runners

Because of the negative health consequences of low energy availability (LEA), researchers have developed criteria based on energy availability (EA) to determine when athletes are at threat of physiological and performance disturbances. The proposed LEA criteria are: ≤30 kcal/kg/LBM/day - high risk, 30-45 kcal/kg/LBM/day - moderate risk and ≥ 45 kcal/kg/LBM/day - no risk (Melin et al., IJSNEM, 2019). These criteria, however, are based almost entirely on White (Caucasian) racial populations. PURPOSE: This study evaluated the prevalence of LEA and its potential impact on the hormonal profile of high-level Kenyan male and female middle- and long-distance runners. METHODS: A cross-sectional observational design approach was used in which high-level Kenyan male and female (n = 30 and n = 26 respectively) middle- and long-distance runners were examined (IAAF scores >1000 points). For LEA, food and training diaries were collected from the participants and exercise energy expenditure was calculated from the VO2max results and training diaries. To be conservative and not underestimate EA, we examined the three highest energy intake days in our analysis, and to compensate for potential underreporting, applied a previously published dietary correction factor (Õnnik et al., EJAP 2021). Resting blood hormonal measurements consisted of luteinizing hormone, follicle-stimulating hormone, prolactin, oestradiol, free thyroxine, thyroid-stimulating hormone, testosterone, triiodothyronine, insulin and cortisol. RESULTS: For the female sample ~ 13% were at no risk, ~31% were at moderate risk, and ~ 66% at a high risk for LEA. For the male sample ~ 4% were at no risk, ~9% were at a moderate risk, and ~ 87% were at a high risk for LEA. The hormonal values observed were variable, but within the normal expected range for healthy men and women in each of the respective measures (Feingold et al., Endotext 2000). CONCLUSIONS: Our main findings were 1) the majority of our runners (men and women) were at high risk for LEA and, 2) surprisingly no abnormalities in the hormonal values were evident even though LEA risk was high and hormonal disturbances are a hallmark of LEA. Perhaps EA criteria for deciding LEA risk level, which are based primarily on White racial populations, are not appropriate for African-based populations.

A novel learning observer-based fault-tolerant attitude control for rigid spacecraft

This paper investigates a learning observer-based fault-tolerant control strategy for a rigid spacecraft attitude system with external disturbance, parameter uncertainty and actuator faults. An adaptive learning observer design approach, which does not require the upper bound information of generalized perturbation, is proposed to estimate the attitude angular velocities and reconstruct actuator faults accurately and quickly. On this basis, a fault tolerant attitude tracking control scheme is developed for spacecraft attitude stabilization by combining the estimation value and backstepping control technique. The stability of the faulty attitude system under the designed fault-tolerant control method is analyzed using Lyapunov framework. Finally, simulations are given to show the effectiveness of the proposed method.

Aperiodic Sampled-Data Takagi–Sugeno Fuzzy Extended State Observer for a Class of Uncertain Nonlinear Systems With External Disturbance and Unmodeled Dynamics

For the extended state observer (ESO) design, the most challenging issue is to exploit efficient nonlinear observation performance, while maintaining desirable linear numerical tractability under noncontinuous transmission. In this article, in order to address this issue, the sampled-data ESO design is investigated for a class of uncertain nonlinear systems. First, based on the fuzzy modeling approach with reasonable fuzzy rules and sets, the nonlinear functions of the ESO are suitably approximated by several local linear models weighted by membership functions. Then, a novel methodology of Takagi–Sugeno fuzzy extended state observer (TSFESO) is developed for the first time. By virtue of fuzzy membership functions, the estimating action is implemented in a nonlinear pattern, while taking advantages of Takagi–Sugeno fuzzy formulation, the observer gains can be calculated in a linear manner. As a result, the nonlinear estimating efficiency and linear numerical tractability are integrated in a unified framework. Second, for the aperiodic sampling case, the exponential convergence criterion for the TSFESO is presented by constructing a sampling- and time-dependent Lyapunov functional, in which the information on sampling action is taken into full consideration for desirable feasibility. Moreover, the observer design approach is also put forward. Finally, the superiorities and effectiveness of the proposed approaches are demonstrated by numerical examples.

Robust adaptive fault detection and diagnosis observer design for a class of nonlinear systems with uncertainty and unknown time-varying internal delay

This paper introduces a novel robust adaptive fault detection and diagnosis (FDD) observer design approach for a class of nonlinear systems with parametric uncertainty, unknown system fault and time-varying internal delays. The conditions for the existence of the proposed FDD are obtained based on the well-known Linear Matrix Inequalities (LMI) technique. Using Lyapunov stability theory, the adaptation laws for updating the observer weights and unknown faults estimation are derived based on which the convergence of the state estimation error to zero and asymptotic stability of the error dynamics are proven. Toward this, a new structural algorithm for FDD observer design is also derived based on LMIs. The performance of the proposed method is also investigated while applying to some industrial systems. Simulation results illustrate superior performance of the proposed method for the systems subject to time-varying unknown delays on states, uncertainty in nonlinear system modeling and unknown system faults.

An Extension of Adaptive State Observers Using Dynamic Regressor Extension and Mixing With Relaxed Excitation Conditions

The recently proposed DREM-based adaptive state observer (DREMBAO) design approach assumes that there exists transformation of the system model into a cascade form, linearly dependent on parameters vector and depends only on measured input and output. This paper proposes an extension to relax that assumption and extend the approach to state affine systems. Like the original version of DREMBAO, the proposed approach ensures global convergence of an estimation error to zero under a relatively weak condition. The advantages of the extension are demonstrated in the example with a permanent magnet synchronous motor. In contrast to the original approach, the proposed extension allows taking into account viscous friction in the motor and obtaining a simplified load torque estimation algorithm. Moreover, finite-time convergence to zero is ensured for the load torque and speed estimation error under a weak interval excitation.