Periodic Disturbances Research Articles

Adaptive containment fault‐tolerant control for saturated nonlinear multiagent systems with multiple faults and periodic disturbances

AbstractThis paper addresses the problem of adaptive containment fault‐tolerant control for nonlinear multiagent systems with periodic disturbances. Different from most existing fault‐tolerant control schemes, the form of multiple faults is explicitly considered in this paper, including actuator faults and sensor faults. By combining the Fourier series expansion with neural networks, the unknown nonlinear dynamics subject to time‐dependent periodic disturbances are approximated. Then, the “complexity of explosion” issue that exists in traditional backstepping‐based results is avoided by introducing a first‐order sliding‐mode differentiator. It is proved that the developed containment control policies can ensure that all signals of the close‐loop systems are uniformly ultimately bounded, and all followers can converge to a convex area formed by multiple leaders. Simulation results verify the validity of the proposed scheme.

Repetitive dynamic matrix control for systems with periodic specifications

This paper proposes a Repetitive Dynamic Matrix Control (RDMC) for systems with periodic specifications. The new algorithm is able to track periodic references and reject repetitive disturbances with a known period based on a modified prediction error. A repetitive version of the Generalized DMC (GDMC) is also proposed such that it can be applied to control open-loop unstable systems. Only the step-response coefficients are required to describe the dynamical system such that the RDMC preserves the modeling simplicity of the Dynamic Matrix Control (DMC). The proposed solution can be interpreted as an extension of the DMC for repetitive control applications. A data-driven filter design is proposed in order to ensure null prediction steady-state error in the presence of periodic disturbances even for unstable open-loop systems. Two case studies are presented to show the usefulness of the proposed strategy for control systems with periodic specification and to illustrate the typical advantages and drawbacks of the proposed repetitive control extension of the DMC algorithm.

Iterative Learning with Adaptive Sliding Mode Control for Trajectory Tracking of Fast Tool Servo Systems

To address the tracking control problem of the periodic motion fast tool servo system (FTS), we propose a control method that combines adaptive sliding mode control with closed-loop iterative learning control. Adaptive sliding mode control enhances the system’s robustness to external non-repetitive disturbances, and exponential gain iterative learning control compensates for the influence of periodic disturbances such as cutting force. The experimental results show that the proposed iterative learning controller based on adaptive sliding mode control can effectively eliminate the influence of various interference factors, achieve accurate tracking of the FTS system’s motion trajectory within a limited number of iterations, and ensure the stability of the system, which has the advantages of a fast convergence speed, high tracking accuracy, and strong robustness.

Research on anti-vibration tension control based on self-coupling fractional-order PID

Constant tension control is essential for excellent winding quality. However, the system’s nonlinearity and external disturbance make it challenging to guarantee tension control accuracy with conventional control methods. Thus, a self-coupling fractional-order proportional–integral–derivative (SC-FOPID) control scheme combined with a disturbance observer is proposed to enhance the system’s anti-vibration performance. The fractional-order dynamic model of the unwinding roller and swing rod is established by analyzing the tension mechanism. Based on deliberate analysis and calculation, the vibration shock signal can be decomposed into periodic sinusoidal disturbance and bounded noise approximately. As such, an output-based anti-vibration method using a fractional-order model can be realized, where a back recursive disturbance observer is designed to estimate the periodic component. Simultaneously, the bounded noise exhibited in vibration can be attenuated by the SC-FOPID controller. The stability is guaranteed using the Lyapunov theorem, and the simulation results show the proposed method’s effectiveness in improving the tension control performance.

A hybrid graph attention network based method for interval prediction of shipboard solar irradiation

Solar energy ships came into being to reduce carbon emissions of global shipping and fossil fuels consumption. Accurate prediction of photovoltaic power generation can improve the economical operation of solar energy ships and reduce the power fluctuation of ship power systems. This study proposes a novel hybrid method to forecast ultra-short-term solar irradiation in a solar energy ship along the east coast of China. An improved graph attention framework is trained to describe the dynamic spatial-temporal topology among five weather stations and a solar energy ship. Initial interval prediction results are then determined by an improved Divided Period Optimization (DPO) method. According to distribution characteristics of the prediction error of shipboard solar irradiation, a Dynamic Prediction Interval Modification (DPIM) method is proposed to further optimize the prediction accuracy and interval width of ultra-short-term solar irradiation. Comparison experiments show that the dynamic connection matrix effectively improves the prediction accuracy, and the DPIM method reduces the PI width of 28.84%–37.79 % in shipboard solar irradiation. The proposed prediction method can accurately predict the shipboard solar irradiation at the period of significant disturbance, and provide effective technical support for the economic scheduling of solar energy ships.

Precipitation Characteristics of Easterly Waves Across the Global Tropics

AbstractTropical easterly waves (TEWs) are a recurrent mode of low‐latitude weather that are often convectively coupled and impact precipitation extremes. Previous work has examined the development of TEWs and their associated precipitation for individual seasons or regional domains, but no studies exist that document the importance of TEW precipitation globally. This study quantifies the precipitation associated with TEWs across the entire tropics using satellite (Integrated Multi‐satellitE Retrievals for the Global Precipitation Measurement [IMERG]) and reanalysis (Modern‐Era Retrospective analysis for Research and Applications, Version 2 [MERRA‐2]) data. Traditional space‐time filtering of precipitation reveals a mostly similar climatological power distribution for westward traveling, synoptic period disturbances corresponding to TEWs within all data sets. Using objective tracking, we find that areas with maximum TEW frequency such as the North Atlantic, Equatorial Pacific, and Indian Ocean have the highest accumulation of TEW‐associated precipitation. TEWs account for at most 30% of total annual precipitation in regions where they commonly occur and 1%–5% over much of the tropics. Vertically collocated storms, where the 850 and 700 hPa tracks correspond with each other, have higher conditional rain rates and indicate that waves with vertical development produce stronger and more organized convection. We find similar regional patterns using MERRA‐2 precipitation and latent heating, although the importance and contribution of TEWs to the background are reduced compared to IMERG. While the broad pattern of TEW associated precipitation in MERRA‐2 is like observations, the underestimation of rainfall contributions from TEWs, coupled with occasional false alarms in reanalysis data, suggests that MERRA‐2 does not capture organized convection within TEWs correctly.

Resilience to periodic disturbances and the long-term genetic stability in Acropora coral

Climate change is restructuring natural ecosystems. The direct impacts of these events on biodiversity and community structure are widely documented, but the impacts on the genetic variation of populations remains largely unknown. We monitored populations of Acropora coral on a remote coral reef system in northwest Australia for two decades and through multiple cycles of impact and recovery. We combined these demographic data with a temporal genetic dataset of a common broadcast spawning corymbose Acropora to explore the spatial and temporal patterns of connectivity underlying recovery. Our data show that broad-scale dispersal and post-recruitment survival drive recovery from recurrent disturbances, including mass bleaching and mortality. Consequently, genetic diversity and associated patterns of connectivity are maintained through time in the broader metapopulation. The results highlight an inherent resilience in these globally threatened species of coral and showcase their ability to cope with multiple disturbances, given enough time to recover is permitted.

Control of a System with Periodic Disturbance using Disturbance Observer and Line Enhancer

Control of a System with Periodic Disturbance using Disturbance Observer and Line Enhancer

Quantifying hurricane impacts on United States Virgin Islands reef fishes using a catchability invariant approach to compare uncalibrated survey indices

The United States Virgin Island's (USVI) coral reefs support many economically and ecologically important fish species. Located in the Caribbean Sea, they are subject to frequent severe weather disturbances, including two category 5 hurricanes, Irma and Maria, in 2017. The overarching goal of this study was to identify reef fish community impacts following these extreme events using discontinuous survey indices. Long-term (2001–2021), in situ, fishery-independent survey data using two methods were standardized to the extent possible in two regions of the USVI, St. Thomas/St. John (STT/STJ) and St. Croix (STX). Comparable data were assessed, 73 species collected on hard- bottom habitat, to identify the number of these species with significant changes in density and/or mean length between 2-yr survey intervals over the historic baseline (2001–2015), disturbance (2017–2019), and postdisturbance (2019–2021) periods. The results varied by region: STT/STJ had no disturbance impact and STX had a significant disturbance impact. In STX, 20 species had significant changes in density in the disturbance period compared to an average of 9.7 (SD 3.8) species for the baseline period. The proportion of species with significant density increases and decreases were similar suggesting that overall disturbance impacts are nuanced. Mean length observations were less informative, likely due to survey method and sample size changes. However, in combination with density they provided useful insights into the possible causes of population change. The successful use of discontinuous survey indices to obtain meaningful biological insights has broader applications to ecosystem and fishery datasets with similar limitations.

Divergent Component of Motion Planning and Adaptive Repetitive Control for Wearable Walking Exoskeletons.

Wearable walking exoskeletons show great potentials in helping patients with neuro musculoskeletal stroke. Key to the successful applications is the design of effective walking trajectories that enable smooth walking for exoskeletons. This work proposes a walking planning method based on the divergent component of motion to obtain a stable joint angle trajectory. Since periodic and nonperiodic disturbances are ubiquitous in the repeating walking motion of an exoskeleton system, a major challenge in the walking control of wearable exoskeleton is the joint angle drift problem, that is, the joint angle motion trajectories are not necessarily periodic due to the presence of disturbance. To address this challenge, this work develops an adaptive repetitive control strategy to guarantee that the motion trajectories of joint angle are repetitive. In particular, by treating the disturbance as system uncertainties, an adaptive controller is designed to compensate for the uncertainties based on an integral-type Lyapunov function. A fully saturated learning approach is then developed to achieve asymptotic tracking of repetitive walking trajectories. Extensive experiments are carried out to demonstrate the effectiveness of the tracking performance.

Development of the Wave Motion Induced by Near-Bottom Periodic Disturbances in a Two-Layer Shear Current

Development of the Wave Motion Induced by Near-Bottom Periodic Disturbances in a Two-Layer Shear Current

Natural streamflow reconstruction and quantification of hydrological drought in the Soan River basin, Pakistan

AbstractClimate change and rapid socioeconomic development have exacerbated the damage caused by hydrological droughts. To ensure effective drought defense and infrastructure development, it is essential to investigate variations in hydrological droughts. The primary objective of this study is to reconstruct the natural streamflow by using Soil and Water Assessment Tool (SWAT) hydrological modeling. The hydrological drought at different time scales (1, 3, 6, and 12 months) were measured using the streamflow drought index (SDI). The statistical parameters, including Nash–Sutcliffe Efficiency and the Coefficient of Determination, which yielded values of 0.84 and 0.82 during the calibration period and 0.78 and 0.76 during the validation period, respectively, showed a satisfactory SWAT model performance. Additionally, the Pettit test was used to identify a change point in streamflow within the 1991–2015 timeframe, leading to the division of the study period into two distinct phases: an undisturbed period (1991–1998) and a disturbed period (1999–2015). The SDI index‐based analysis revealed 9.39% moderate drought and 3.13% severe drought during the undisturbed period, while 11.76% moderate drought and 7.35% severe drought may happen due to the human influences that occurred in the disturbed period. These findings enhance the understanding of the hydrological drought variations in the Soan River basin for optimizing the water resources management system and effectively preventing and mitigating drought‐related damages.

Modelling of anaerobic digestion of microalgae biomass: Effect of overloading perturbation

Anaerobic digestion (AD) of microalgae is an intriguing approach for bioenergy production. The scaling-up of AD presents a significant challenge due to the systematic efficiency losses related to process instabilities. To gain a comprehensive understanding of AD behavior, this study assessed a modified version of the anaerobic digestion model No1 (ADM1) + Contois kinetics to represent microalgae AD impacted by overloading. To this end, two new inhibition functions were implemented: inhibition by acetate for acidogenesis/acetogenesis and total volatile fatty acids for hydrolysis. This proposed ADM1 modification (including Contois kinetics) simulated AD behavior during the stable, disturbed and recovery periods, showing that the inhibition functions described in the original ADM1 cannot explain the AD performance under one of the most common perturbations at industrial scale (overloading). The findings underscore the importance of refining the inhibitions present in original ADM1 to better capture and predict the complexities of microalgae AD against overloading.

Analyzing Unsteady Turbomachinery Flow Simulations With Mixing Entropy

Abstract The prediction of unsteady aerodynamic loads is a central problem during the design of turbomachinery. Over the last 20 years, harmonic balance methods have been shown to be highly efficient for this task. A CPU-cost optimal setup of a harmonic balance simulation, however, requires knowledge of relevant harmonics. In the case of a single blade row with a periodic disturbance this question amounts to the classical problem of harmonic convergence, a problem which is solely due to the nonlinearity of the unsteady flow physics. In contrast, for multi-stage configurations, the choice of harmonics is further complicated by the fact that the interactions of disturbances with blade rows may give rise to a vast spectrum of harmonics that possibly have important modal content, e.g., Tyler–Sofrin modes. The aim of this paper is to show that the mixing entropy attributed to circumferential modes of a given harmonic can serve as a disturbance metric on the basis of which a criterion could be derived whether a certain harmonic should be included or not. The idea is based on the observation that the entropy due to the temporal and circumferential mixing of the flow at a blade row interface may be decomposed, up to third-order terms, into independent contributions from different frequencies and mode orders. For a given harmonic balance (and steady) flow result, the mixing entropy attributed to modes that are simply mixed out, rather than resolved in the neighboring row, is shown to be a natural indicator of a potential inaccuracy. We present important features of the mixing entropy for unsteady disturbances, in particular a close relationship to sound power for acoustic modes. The problem of mode selection in a 1.5-stage compressor configuration serves as a practical example to illustrate our findings.

Robust [formula omitted] control of singular networked cascade control systems with norm-bounded uncertainty and periodic DoS attack

In this article, the topic of event-triggered H∞ control is investigated for a singular networked cascade control system (SNCCS) under periodic DoS attacks, norm-bounded uncertainty, and external disturbances. Unlike existing articles, the SNCCS is assumed to be singular not only in the inner loop but also in the outer loop. Then, using Multiple Lyapunov Functionals (MLF), new sufficient conditions are derived for the admissibility of the SNCCS through linear matrix inequalities, guaranteeing the regularity and impulse-freeness of the system. Afterward, state-feedback controllers are designed for both the inner and the outer loops of the system. All the derived theories in this article can be utilized for stabilizing both singular and non-singular NCCSs. Finally, simulation results are presented on a steam generation process in a power plant to validate the proposed method.

Performance recovery-based adaptive saturated fault-tolerant control of uncertain nonlinear systems with actuator switching and periodic disturbances

This paper studies an adaptive saturated fault-tolerant control problem for uncertain nonlinear systems with periodic disturbances. In contrast to previous fault-tolerant control methods, a case of deferred actuator switching is taken into account, which stands for a more common situation. By designing monitoring functions and reconfigurable controllers, tracking errors can be recovered to prescribed performance within a specified time after a fault is detected. Then, a low-computation control strategy is employed to address the problem of complexity explosion, and neural networks and Fourier series expansion are combined to model the uncertain nonlinear dynamics subject to time-varying periodic disturbances. The proposed scheme has a simpler structure and ensures the boundedness of all signals within the closed-loop system. Finally, to verify the effectiveness of the design scheme, two simulation examples are provided.

Ostracods response to environmental anthropogenic disruption in a neotropical karstic lake in southern Mexico

Ostracods are sensitive to environmental changes and represent a powerful tool to assess anthropogenic impact such as land use changes and deforestation. In this work we present ostracod, ephippia, diatom and geochemical data of Lake San Lorenzo sediments dating from 1956 to 2013. The ostracod assemblage consists of Darwinula stevensoni, Cypridopsis okeechobei, Cytheridella ilosvayi and an unidentified species. This Unknown species rapidly adapted to the new environmental conditions of enhanced nutrients levels and variable oxygen, whereas the other ostracods were absent in the sediments dating from around 1982 to 1992. Overall, D. stevensoni, C. okeechobei and C. ilosvayi are benthic species that occur in shallow waters or littoral zones with rich vegetation. However, we suggest C. ilosvayi was the most sensitive to oxygen variations as it is only present in sediments dating to ∼1978. The lack of ostracod preservation in the sedimentary record, especially during ∼1995–2013 could be result of anoxic lake bottom conditions caused by high organic matter content during periods of anthropogenic catchment disturbance. Finally, we suggest that analysis and description of live specimens with soft parts of the Unknown species are strongly necessary to determine this species and its environmental preferences.

Brazilian savannah tree as bio-inspiration for hydraulic transient control in a penstock of a small hydropower plant

This study proposes an innovation, which is to use a non-circular and bio-inspired forced conduit (a new penstock with a cross section inspired by a tree trunk), to control the effects of hydraulic transients in Brazilian small hydropower plants (SHPs). The aim is to demonstrate that natural structures, adapted to periodic environmental disturbances, are better at hydraulic transient control than traditional conduits. The proposed methodology includes the following steps: (1) problem identification; (2) potential biological model identification; (3) development of alternatives; (4) implementation and testing; and (5) solution selection. This research was conducted at the São Tadeu I SHP, in the city of Santo Antônio de Leverger/MT, Brazil. The following tree biological models from the Brazilian savannah (Cerrado) were used: Handroanthus capitatus and Strychnos pseudoquina. The proposed innovation improves the conduit of the traditional circular section and the relief valve solution of the criteria studied. The reason for this improvement was the reduction of wave speed in the non-circular section (from 1126 to 583 m s−1).

Adaptive Active Disturbance Rejection Control for Uncertain Current Ripples Suppression of PMSM Drives

Under complex working conditions, there are uncertain periodic and aperiodic disturbances in the curr- ent loop of permanent magnet synchronous motor (PMSM) drives. These uncertain disturbances can lead to uncertain current ripples, deteriorating the current loop performance. To deal with the problem, this paper proposes an adaptive active disturbance rejection control (ADRC) for the current loop to suppress the uncertain current ripples. In the ada- ptive ADRC, the extended state observer is optimized by the adaptive resonant controller so that it can estimate both the uncertain periodic and aperiodic disturbances. Thus, the adaptive ADRC can suppress both the uncertain periodic and aperiodic disturbances to attenuate the uncer- tain current ripples in the current loop, and it does not need the disturbance information. In addition, the stability of the observer in the adaptive ADRC is systematically analyzed by the singular perturbation theory and the averaging theorem. Finally, the effectiveness of the adaptive ADRC is validated on a 2.2-kW PMSM platform.

Improved ADRC With a Cascade Extended State Observer Based on Quasi-Generalized Integrator for PMSM Current Disturbances Attenuation

Traditional active disturbance rejection control (ADRC) is not adequately capable to deal with current disturbances including periodic harmonics of permanent magnet synchronous motor (PMSM). Thus, an improved ADRC with a cascade extended state observer (CESO) based on quasi-generalized integrator (QGI) is proposed to attenuate the periodic and aperiodic disturbances in the current loop. In the proposed strategy, a CESO with two cascaded levels is designed to enhance the estimation accuracy of aperiodic disturbances and decrease the steady-state observation error of periodic harmonics. The QGI is embedded into the second cascade level of CESO to improve its estimation accuracy harmonic disturbances. With the periodic harmonics accurately estimated, the subsequent improved ADRC based on feedback control law can effectively enhance the rejection of such disturbances. The theoretical analysis is comprehensively conducted to investigate the disturbances estimation performance, stability, disturbances rejection capability and robustness, while the parameter tuning strategy is studied based on the control bandwidth. Finally, the effectiveness and superiority of the proposed scheme are verified on a PMSM bench through the experiments.