Pre-defined Performance Research Articles

Generalized modulation for distance-aware optical camera communication beyond oversampled and undersampled schemes

Oversampled modulation (OM) and undersampled modulation (UM) are two commonly used optical camera communication (OCC) modulation schemes for high-speed communication in short-range and reliable communication at long distances, respectively. However, the relationship between these two schemes and the tradeoff in performance for arbitrary communication distances have not been thoroughly investigated. In this study, we analyze the impact of distance and modulation parameters on pixel efficiency and packet delivery rate performance, demonstrating the underlying unity of traditional OM and UM schemes. Furthermore, we propose a generalized modulation scheme that allows for achieving predefined link performance at a given distance by adjusting the modulation parameters, such as packet length and repetition counts. Simulation and experimental results show that the proposed generalized modulation scheme provides OCC with a unique distance-aware capability other than the traditional OM and UM schemes, which are two special cases focusing on effectiveness and reliability, respectively. This research enhances our understanding of OCC data modulation and establishes a theoretical foundation for achieving efficient and reliable OCC transmission in complex environments.

Assessment of strategic healthcare purchasing and financial autonomy in Tanzania: the case of results-based financing and health basket fund.

Low-and middle-income countries (LMICs) are implementing health financing reforms toward Universal Health Coverage (UHC). In Tanzania direct health facility financing of health basket funds (DHFF-HBF) scheme was introduced in 2017/18, while the results-based financing (RBF) scheme was introduced in 2016. The DHFF-HBF involves a direct transfer of pooled donor funds (Health Basket Funds, HBF) from the central government to public primary healthcare-PHC (including a few selected non-public PHC with a service agreement) facilities bank accounts, while the RBF involves paying providers based on pre-defined performance indicators or targets in PHC facilities. We consider whether these two reforms align with strategic healthcare purchasing principles by describing and comparing their purchasing arrangements and associated financial autonomy. We used document review and qualitative methods. Key policy documents and articles related to strategic purchasing and financial autonomy were reviewed. In-depth interviews were conducted with health managers and providers (n = 31) from 25 public facilities, health managers (n = 4) in the Mwanza region (implementing DHFF-HBF and RBF), and national-level stakeholders (n = 2). In this paper, we describe and compare DHFF-HBF and RBF in terms of four functions of strategic purchasing (benefit specification, contracting, payment method, and performance monitoring), but also compare the degree of purchaser-provider split and financial autonomy. Interviews were recorded, transcribed verbatim, and analyzed using a thematic framework approach. The RBF paid facilities based on 17 health services and 18 groups of quality indicators, whilst the DHFF-HBF payment accounts for performance on two quality indicators, six service indicators, distance from district headquarters, and population catchment size. Both schemes purchased services from PHC facilities (dispensaries, health centers, and district hospitals). RBF uses a fee-for-service payment adjusted by the quality of care score method adjusted by quality of care score, while the DHFF-HBF scheme uses a formula-based capitation payment method with adjustors. Unlike DHFF-HBF which relies on an annual general auditing process, the RBF involved more detailed and intensive performance monitoring including data before verification prior to payment across all facilities on a quarterly basis. RBF scheme had a clear purchaser-provider split arrangement compared to a partial arrangement under the DHFF-HBF scheme. Study participants reported that the RBF scheme provided more autonomy on spending facility funds, while the DHFF-HBF scheme was less flexible due to a budget ceiling on specific spending items. Both RBF and DHFF-HBF considered most of the strategic healthcare purchasing principles, but further efforts are needed to strengthen the alignment towards UHC. This may include further strengthening the data verification process and spending autonomy for DHFF-HBF, although it is important to contain costs associated with verification and ensuring public financial management around spending autonomy.

Designing an adaptive and deep learning based control framework for modular production systems

In today’s rapidly changing production landscape with increasingly complex manufacturing processes and shortening product life cycles, a company’s competitiveness depends on its ability to design flexible and resilient production processes. On the shop-floor, in particular, the production control plays a crucial role in coping with disruptions and maintaining system stability and resilience. To address challenges arising from volatile sales markets or other factors, deep learning algorithms have been increasingly applied in production to facilitate fast-paced operations. In particular deep reinforcement learning frequently surpassed conventional and intelligent approaches in terms of performance and computational efficiency and revealed high levels of control adaptability. However, existing approaches were often limited in scope and scenario-specific, which hinders a seamless transition to other control optimization problems. In this paper, we propose a flexible framework that integrates a deep learning based hyper-heuristic into modular production to optimize pre-defined performance indicators. The framework deploys a module recognition and agent experience sharing, enabling a fast initiation of multi-level production systems as well as resilient control strategies. To minimize computational and re-training efforts, a stack of trained policies is utilized to facilitate an efficient reuse of previously trained agents. Benchmark results reveal that our approach outperforms conventional rules in terms of multi-objective optimization. The simulation framework further encourages research in deep-learning-based control approaches to leverage explainability.

Trajectory tracking control of an autonomous underwater helicopter with improved prescribed performance

Aiming at the high-precision trajectory tracking problem of an autonomous underwater helicopter (AUH) under conditions of environmental disturbances, thruster loss and floating error, a prescribed performance control method based on a novel performance function is designed and can be applied in ultra-mobility tasks. The com bination of the proposed new performance function and the constraint inequality avoids large overshoot in the initial period of system and allows the expected convergence time to be set artificially. The thruster loss, expressed in thrust distribution matrix, is incorporated into general uncertainty with external disturbances. In addition, the extended state observer (ESO) is used to compensate the unknown states, providing a reference for the estimation of upper bound of general uncertainty. Simulation results show that the proposed control scheme is able to guarantee the pre-defined tracking performance limited by performance functions under general uncertainty.

A genetic programming-based optimal sensor placement for greenhouse monitoring and control.

Optimal sensor location methods are crucial to realize a sensor profile that achieves pre-defined performance criteria as well as minimum cost. In recent times, indoor cultivation systems have leveraged on optimal sensor location schemes for effective monitoring at minimum cost. Although the goal of monitoring in indoor cultivation system is to facilitate efficient control, most of the previously proposed methods are ill-posed as they do not approach optimal sensor location from a control perspective. Therefore in this work, a genetic programming-based optimal sensor placement for greenhouse monitoring and control is presented from a control perspective. Starting with a reference micro-climate condition (temperature and relative humidity) obtained by aggregating measurements from 56 dual sensors distributed within a greenhouse, we show that genetic programming can be used to select a minimum number of sensor locations as well as a symbolic representation of how to aggregate them to efficiently estimate the reference measurements from the 56 sensors. The results presented in terms of Pearson's correlation coefficient (r) and three error-related metrics demonstrate that the proposed model achieves an average r of 0.999 for both temperature and humidity and an average RMSE value of 0.0822 and 0.2534 for temperate and relative humidity respectively. Conclusively, the resulting models make use of only eight (8) sensors, indicating that only eight (8) are required to facilitate the efficient monitoring and control of the greenhouse facility.

Clinical evidence requirements according to the IVDR 2017/746: practical tools and references for underpinning clinical evidence of IVD-MDs.

In May 2022, the European Regulation 2017/746 (IVDR) came into force. It changes the approach of invitro medical devices (IVD-MDs) for industry and institutions. It reinforces the clinical evidence requirements to improve performance, safety and transparency. Despite extended transition periods and existing guides, IVDR remains difficult to interpret and bringing devices into compliance requires efforts. The generation of clinical evidence is essential to demonstrate compliance with IVDR, and encompasses scientific validity, analytical performance and clinical performance. It is required to demonstrate, per intended use in the target population and clinical care pathway, IVD-MDs clinical performance (compared to a predefined clinical performance). Thus, there is a need for IVD-manufacturers and end-users inhealth care institutions, to obtain guidance on how to generate this clinical evidence. This article aims industrials and clinicians to identify key steps imposed by the IVDR for bringing IVD-MDs to the EU-market. We propose a general view of performance evaluation requirements for IVD-MDs and provide key references, including how to establish study design that will enable to document clinical performance of existing, refined or emerging medical tests. Finally, we propose a roadmap to address the relevant questions and studies in relation to the documents requested in the IVDR.

Performance of an artificial intelligence automated system for diabetic eye screening in a large English population.

A diabetic eye screening programme has huge value in reducing avoidable sight loss by identifying diabetic retinopathy at a stage when it can be treated. Artificial intelligence automated systems can be used for diabetic eye screening but are not employed in the national English Diabetic Eye Screening Programme. The aim was to report the performance of a commercially available deep-learning artificial intelligence software in a large English population. 9817 anonymised image sets from 10,000 consecutive diabetic eye screening episodes were presented to an artificial intelligence software. The sensitivity and specificity of the artificial intelligence system for detecting diabetic retinopathy were determined using the diabetic eye screening programme manual grade according to national protocols as the reference standard. For no diabetic retinopathy versus any diabetic retinopathy, the sensitivity of the artificial intelligence grading system was 69.7% and specificity 92.2%. The performance of the artificial intelligence system was superior for no or mild diabetic retinopathy versus significant or referrable diabetic retinopathy with a sensitivity of 95.4% and specificity of 92.0%. No cases were identified in which the artificial intelligence grade had missed significant diabetic retinopathy. The performance of a commercially available deep-learning artificial intelligence system for identifying diabetic retinopathy in an English national Diabetic Eye Screening Programme is presented. Using the pre-defined settings artificial intelligence performance was highest when identifying diabetic retinopathy which requires an action by the screening programme.

Multi-institutional prostate cancer unit of Padova: Review of activity and performance indicators of the first 18 months after ISO9001 certification.

337 Background: The development of Prostate Cancer Units (PCUs) determined a paradigm shift in the treatment of this disease based on multidisciplinary management and shared clinical pathways among several specialists, but activities of PCUs are rarely reported. The Multi-Institutional PCU of Padova was decreed on Nov 2020 and involves Istituto Oncologico Veneto (IOV IRCCS), Azienda Ospedaliera-University of Padova (AOPD UNIPD) and Casa di Cura of Abano Terme. Padova PCU achieved the ISO 9001 certification on Dec 2020 and performance indicators were identified. Methods: We assessed clinical indicators of coordination, process and outcome of our PCU from 1st Jan 2021 to 30 Jun 2022. Data were extracted from the Electronic Medical Record ONCOSYS and from HEALTHMEETING, the software dedicated to register clinical information of patients, shared therapeutic decisions and participation of specialists to the PCU meetings. Results: A total of 739 consecutive pts were managed by the PCU in 18 months, generating a total of 1002 case discussions in 76 meetings, for a mean of 12,8 case discussions per week. Three Urology units performed 500 prostatectomies per year. Presence of at least one specialist for each core team specialty (either in presence of teleconference) was almost 100% with the exception of the pathologists, who were consulted mainly on demand. Waiting time for case discussion was always less than 2 weeks. Pts were presented by urologist, oncologist, radiation oncologist or other specialist in 46,3, 39,8, 10,5 and 3,4% of cases, respectively. They had localized/locally advanced, biochemically recurrent, metastatic castration-sensitive or castration-resistant disease in 43.3, 8, 28.2 and 20.5% of cases, respectively. Decision by the PCU was eventually carried out in 75,5% of cases, was changed due to pt’s preference of other reasons in 6.5%, or was still pending or not assessable in 18% of cases. Median time to completion of pathology report of prostatic biopsies was 8 days, median time from surgery to adjuvant radiotherapy was 5 months. Clinical trials with investigational drugs were proposed to 17% of pts with metastatic disease. Several process and outcome indicators (e.g., rate of active surveillance, rate of combined systemic therapy in men with metastatic castration sensitive cancer, survival of patients with metastatic castration resistant disease, etc.) could not be verified yet because they could not be extracted as aggregate data from institutional software and administrative databases. Conclusions: The volumes of Padova PCU and participation rate of core team specialists fulfill international requirements. Institutional software should be implemented in order to allow for aggregate data collection for the assessment of pre-defined performance indicators of PCU instead of reviewing the clinical chart of each prostate cancer pt.

Event-trigger-based Fault-tolerant Control of Uncertain Non-affine Systems with Predefined Performance

Event-trigger-based Fault-tolerant Control of Uncertain Non-affine Systems with Predefined Performance

MyProstateScore in men considering repeat biopsy: validation of a simple testing approach

BackgroundMen with persistent risk of Grade Group (GG) ≥ 2 cancer after a negative biopsy present a unique clinical challenge. The validated MyProstateScore test is clinically-available for pre-biopsy risk stratification. In biopsy-naïve patients, we recently validated a straightforward testing approach to rule-out GG ≥ 2 cancer with 98% negative predictive value (NPV) and 97% sensitivity. In the current study, we established a practical MPS-based testing approach in men with a previous negative biopsy being considered for repeat biopsy.MethodsPatients provided post-digital rectal examination urine prior to repeat biopsy. MyProstateScore was calculated using the validated, locked model including urinary PCA3 and TMPRSS2:ERG scores with serum PSA. In a clinically-appropriate primary (i.e., training) cohort, we identified a lower (rule-out) threshold approximating 90% sensitivity and an upper (rule-in) threshold approximating 80% specificity for GG ≥ 2 cancer. These thresholds were applied to an external validation cohort, and performance measures and clinical outcomes associated with their use were calculated.ResultsMyProstateScore thresholds of 15 and 40 met pre-defined performance criteria in the primary cohort (422 patients; median PSA 6.4, IQR 4.3–9.1). In the 268-patient validation cohort, 25 men (9.3%) had GG ≥ 2 cancer on repeat biopsy. The rule-out threshold of 15 provided 100% NPV and sensitivity for GG ≥ 2 cancer and would have prevented 23% of unnecessary biopsies. Use of MyProstateScore >40 to rule-in biopsy would have prevented 67% of biopsies while maintaining 95% NPV. In the validation cohort, the prevalence of GG ≥ 2 cancer was 0% for MyProstateScore 0–15, 6.5% for MyProstateScore 15–40, and 19% for MyProstateScore >40.ConclusionsIn patients who previously underwent a negative prostate biopsy, the MyProstateScore values of 15 and 40 yielded clinically-actionable rule-in and rule-out risk groups. Using this straightforward testing approach, MyProstateScore can meaningfully inform patients and physicians weighing the need for repeat biopsy.

Quantitative Design for the Battery Equalizing Charge/Discharge Controller of the Photovoltaic Energy Storage System

The purpose of this paper is to develop a photovoltaic module array with an energy storage system that has equalizing charge/discharge controls for regulating the power supply to the grid. Firstly, the boost converter is used in conjunction with maximum power point tracking (MPPT) such that the photovoltaic module array (PVMA) can output maximum power at any time. The battery equalizing charge/discharge architecture is composed of multiple sets of bidirectional buck–boost soft-switching converters in serial connection in order to achieve zero-voltage switching (ZVS) and zero-current switching (ZCS) so that when the charge/discharge power is above 150 W, the converter efficiency can be increased by 3%. The voltage and current signals from the battery are captured and input into the digital signal processor (DSP) to establish an equalizing charge/discharge control rule. For the output voltage control of the bidirectional buck–boost soft-switching converter, the dynamic mode is derived by first using the step response at chosen operating point, then quantitatively designing the controller parameters for the converter, so that the output voltage response can meet the pre-defined performance specifications. Finally, actual test results prove that the equalizing charge/discharge time of the quantitative design controller is shortened by more than 10% when compared to the traditional proportional-integral (P-I) controller regardless of charging or discharging; this also proves that the design of the photovoltaic module array with an energy storage system (ESS) that has equalizing charge/discharge controls is valid.

Multistage power and energy management strategy for hybrid microgrid with photovoltaic production and hydrogen storage

For several years, microgrids (MGs) integrated with smart grids have been presented as one of the promising solutions for better integration of intermittent renewable energy sources (RES). As a result, the interest for the development of MGs has increased. Due to the variability of RES as well as the non-synchronization of intermittent RES production and energy consumption, new storage systems have emerged. The integration of hydrogen produced via water electrolysis powered by RES, the production of electricity through fuel cells (FCs) and the storage of hydrogen are becoming more and more attractive. In this paper, a multistage power and energy management strategy (MSPEMS) is presented for a MG with photovoltaic (PV) as a RES and a battery energy storage system, a FC and an Electrolyzer. The objective is to solve a unit commitment problem considering the different constraints of the MG components. The power management system (PMS) is based on a Distributed explicit model predictive control (DeMPC), whereas the energy management system (EMS) relies on a mixed-integer quadratic programming (MIQP) optimization problem. The interaction between the power management system (PMS) and the energy management system (EMS) is analyzed in order to improve their effectiveness. The PMS and the EMS are almost always developed separately and their interaction is not investigated. This point is an important contribution to the scientific community and the development of hybrid installations with intermittent sources, especially for hydrogen technologies. The performance of the power and energy management strategy (PEMS) is evaluated using simulation results and different predefined key performance indicators (KPI). The performance analysis shows that the proposed MSPEMS avoid inadequate start-up of the FC and the Electrolyzer.

Low-Complexity Leader-Following Formation Control of Mobile Robots Using Only FOV-Constrained Visual Feedback

This article aims to solve the problem of formation control of mobile robots based on image and provide a low-cost as well as ease-of-implementation solution for mobile robots relying merely on a monocular camera under field-of-view (FOV) constraints. A low-complexity image-based visual servo controller is proposed, which can achieve the desired relative position on the image plane and solve the FOV constraints without the feature depth and leader’s velocities information. To facilitate the control design, a state transformation is first performed to decouple the visual motion kinematics. Then, an error transformation is introduced to handle the FOV constraints, and performance specifications are incorporated in the error transformation to achieve the predefined control performance. Finally, a simple static controller is derived using only information from images, and the stability of the uncertain system with unknown control direction/coefficients under the given performance control condition is analyzed. The effectiveness and performance of the proposed visual servoing controller can be illustrated using both simulations and experiments.

A risk-based evaluation of direct displacement-based design

Recent seismic design approaches developed under the umbrella of performance-based earthquake engineering (PBEE) pursue pre-defined performance objectives in terms of structural response, economic losses, or casualties. The earlier PBEE methods were mainly concerned with the deterministic evaluation of performance at a single ground motion intensity level. This premise, however, provides little insight into the long-term risk-based performance of a structure, and limits the ability to make informed design decisions. Given the inherent sources of uncertainty in all aspects of seismic design, probability theory needs to be employed to enable reliable design solutions. However, applying a risk-oriented design approach is not currently feasible for most practitioners, making it essential to understand how the current deterministic applications of these intensity-based PBEE approaches perform in terms of risk. Specifically, the aim is to investigate the capability of the direct displacement-based design (DDBD) method in producing reliable, risk-consistent designs. A probabilistic PBEE assessment framework is applied as the benchmark to determine the risk of exceeding performance objectives for multiple DDBD-based reinforced-concrete-wall and dual reinforced-concrete-wall/steel-frame buildings located at three different sites. The significant variation in the achieved risk estimates related to the limit states of damage limitation, life safety and global collapse for the buildings considered, questions the ability of DDBD—or any other intensity-based design method that does not account for uncertainty—to offer risk consistency.

Out of hospital cardiac arrest: experience of a bystander CPR training program in Karachi, Pakistan

BackgroundNearly 90% of out-of-hospital cardiac arrest (OHCA) patients are witnessed, yet only 2.3% received bystander cardiopulmonary resuscitation (CPR) in Pakistan. This study aimed to determine retention of knowledge and skills of Hands-Only CPR among community participants in early recognition of OHCA and initiation of CPR in Karachi, Pakistan.MethodsPre and post-tests were conducted among CPR training participants from diverse non-health-related backgrounds from July 2018 to October 2019. Participants were tested for knowledge and skills of CPR before training (pre-test), immediately after training (post-test), and 6 months after training (re-test). All the participants received CPR training through video and scenario-based demonstration using manikins. Post-training CPR skills of the participants were assessed using a pre-defined performance checklist. The facilitator read out numerous case scenarios to the participants, such as drowning, poisoning, and road traffic injuries, etc., and then asked them to perform the critical steps of CPR identified in the scenario on manikins. The primary outcome was the mean difference in the knowledge score and skills of the participants related to the recognition of OHCA and initiation of CPR.ResultsThe pre and post-tests were completed by 652 participants, whereas the retention test after 6 months was completed by 322 participants. The mean knowledge score related to the recognition of OHCA, and initiation of CPR improved significantly (p < 0.001) from pre-test [47.8/100, Standard Deviation (SD) ±13.4] to post-test (70.2/100, SD ±12.1). Mean CPR knowledge after 6 months (retention) reduced slightly from (70.2/100, ±12.1) to (66.5/100, ±10.8). CPR skill retention for various components (check for scene safety, check for response, check for breathing and correct placement of the heel of hands) deteriorated significantly (p < 0.001) from 77.9% in the post-test to 72.8% in re-test. Participants performed slightly better on achieving an adequate rate of chest compressions from 73.1% in post-test to 76.7% in re-test (p 0.27).ConclusionCommunity members with non-health backgrounds can learn and retain CPR skills, allowing them to be effective bystander CPR providers in OHCA situations. We recommend mass population training in Pakistan for CPR to increase survival from OHCA.

An in-silico analysis of electrically evoked responses of midget and parasol retinal ganglion cells in different retinal regions

Objective. Visual outcomes provided by present retinal prostheses that primarily target retinal ganglion cells (RGCs) through epiretinal stimulation remain rudimentary, partly due to the limited knowledge of retinal responses under electrical stimulation. Better understanding of how different retinal regions can be quantitatively controlled with high spatial accuracy, will be beneficial to the design of micro-electrode arrays and stimulation strategies for next-generation wide-view, high-resolution epiretinal implants. Approach. A computational model was developed to assess neural activity at different eccentricities (2 mm and 5 mm) within the human retina. This model included midget and parasol RGCs with anatomically accurate cell distribution and cell-specific morphological information. We then performed in silico investigations of region-specific RGC responses to epiretinal electrical stimulation using varied electrode sizes (5–210 µm diameter), emulating both commercialized retinal implants and recently developed prototype devices. Main results. Our model of epiretinal stimulation predicted RGC population excitation analogous to the complex percepts reported in human subjects. Following this, our simulations suggest that midget and parasol RGCs have characteristic regional differences in excitation under preferred electrode sizes. Relatively central (2 mm) regions demonstrated higher number of excited RGCs but lower overall activated receptive field (RF) areas under the same stimulus amplitudes (two-way analysis of variance (ANOVA), p < 0.05). Furthermore, the activated RGC numbers per unit active RF area (number-RF ratio) were significantly higher in central than in peripheral regions, and higher in the midget than in the parasol population under all tested electrode sizes (two-way ANOVA, p < 0.05). Our simulations also suggested that smaller electrodes exhibit a higher range of controllable stimulation parameters to achieve pre-defined performance of RGC excitation. An empirical model: I = a · exp (b · D) + c of the stimulus amplitude (I)–electrode diameter (D) relationship was constructed to achieve the pre-defined objective function values in different retinal regions, indicating the ability of controlling retinal outputs by fine-tuning the stimulation amplitude with different electrode sizes. Finally, our multielectrode simulations predicted differential neural crosstalk between adjacent electrodes in central temporal and peripheral temporal regions, providing insights towards establishing a non-uniformly distributed multielectrode array geometry for wide-view retinal implants. Significance. Stimulus–response properties in central and peripheral retina can provide useful information to estimate electrode parameters for region-specific activation by retinal stimulation. Our findings support the possibility of improving the performance of epiretinal prostheses by exploring the influence of electrode array geometry on activation of different retinal regions.

Safety and effectiveness of introducing a robotic-assisted percutaneous coronary intervention program in a tertiary center: a prospective study.

Robotic-assisted percutaneous coronary intervention (PCI) is a novel technology that permits remote operation of interventional devices. However, little is known about the safety and effectiveness of introducing a robotic PCI program in a hospital already experienced in traditional coronary angioplasty. Prospective single-arm survey to assess the safety and effectiveness of robotic-assisted PCI in comparison to pre-defined performance goals. The study cohort comprised all consecutive cases treated with robotic PCI since its introduction. The safety primary endpoint was a composite of (I) overall death or (II) non-fatal adverse events related to target vessel complications (stent thrombosis, myocardial infarction, vessel perforation or cardiac tamponade, or repeat invasive treatment) during the index hospitalization. The efficacy primary endpoint was robotic-assisted procedural success, a composite of (I) successful dilatation of the target lesion and (II) successful robotic assistance, defined as absent non-planned manual conversion. A total of 83 patients and 112 lesions were prospectively enrolled. The rate of angiographic success was 99.1%. From these, 97 lesions (86.6%) were treated with only robotic PCI or with hybrid according to the pre-interventional plan. The rates of efficacy and safety primary endpoints were 85.7% and 2.4% respectively (P<0.01 for non-inferior to the pre-defined performance threshold). Introduction of robotic-assisted PCI in a tertiary center was associated with safe and effective results, comparable to pre-defined goals of optimal performance.

Adaptive Fixed-Time Control of Error-Constrained Pure-Feedback Interconnected Nonlinear Systems

This article addresses the problem of decentralized adaptive fuzzy fixed-time control for a class of pure-feedback interconnected nonlinear systems with full-state tracking error constraints. The fuzzy logic systems (FLSs) are adopted to model the unknown nonlinear functions. Combining the properties of the prescribed performance functions (PPFs) with barrier Lyapunov functions (BLFs), the predefined state tracking error dynamic performance and good tracking accuracy are guaranteed. Then, on the basis of the backstepping recursive design technique, a structurally simple adaptive fuzzy fixed-time controller is designed. Furthermore, by the fixed-time stability criterion and the Lyapunov stability theory, it is proven that the boundedness of system signals is guaranteed, and the full-state tracking errors can evolve within the prescribed performance regions within the fixed time. Finally, the effectiveness of the proposed control strategy is demonstrated by some simulation results.

Prescribed Performance Synchronization Control of Chaotic Systems with Unknown Control Gain Signs

For a class of uncertain nonlinear chaotic systems with unknown control gain signs and saturated input, by means of Nussbaum function, a scheme of finite-time prescribed performance synchronization control is proposed. Here, Nussbaum function is used to eliminate the influence of unknown control gain signs, and fuzzy logic systems are used to estimate unknown functions. Lyapunov theory is used to prove that all synchronization errors converge to a predefined small performance range under the designed control method. Finally, simulation results are provided to illustrate the feasibility of the proposed method.

Prescribed Performance-Based Event-Driven Fault-Tolerant Robust Attitude Control of Spacecraft under Restricted Communication

This paper explores the problem of attitude stabilization of spacecraft under multiple uncertainties and constrained bandwidth resources. The proposed control law is designed by combining the sliding mode control (SMC) technique with a prescribed performance control (PPC) method. Further, the control input signal is executed in an aperiodic time framework using the event-trigger (ET) mechanism to minimize the control data transfer through a constrained wireless network. The SMC provides robustness against inertial uncertainties, disturbances, and actuator faults, whereas the PPC strategy aims to achieve a predefined system performance. The PPC technique is developed by transforming the system attitude into a new variable using the prescribed performance function, which acts as a predefined constraint for transient and steady-state responses. In addition, the ET mechanism updates the input value to the actuator only when there is a violation of the triggering rule; otherwise, the actuator output remains at a fixed value. Moreover, the proposed triggering rule is constituted through the Lyapunov stability analysis. Thus, the proposed approach can be extended to a broader class of complex nonlinear systems. The theoretical analyses prove the uniformly ultimately bounded stability of the closed-loop system and the non-existence of the Zeno behavior. The effectiveness of the proposed methodology is also presented along with the comparative studies through simulation results.