Stability Of Systems Research Articles

Driving Role of Zinc Oxide Nanoparticles with Different Sizes and Hydrophobicity in Metabolic Response and Eco-Corona Formation in Sprouts (Vigna radiata).

Zinc oxide nanoparticles (ZnO NPs) cause biotoxicity and pose a potential ecological threat; however, their effects on plant metabolism and eco-corona evolution between NPs and organisms remain unclear. This study clarified the molecular mechanisms underlying physiological and metabolic responses induced by three different ZnO NPs with different sizes and hydrophobicity in sprouts (Vigna radiata) and explored the critical regulation of eco-corona formation in root-nano systems. Results indicated that smaller-sized ZnO inhibited root elongation by up to 37.14% and triggered oxidative burst and apoptosis. Metabolomics confirmed that physiological maintenance after n-ZnO exposure was mainly attributed to the effective stabilization of nitrogen fixation and defense systems by biotransformation of the flavonoid pathway. Larger-sized or hydrophobic group-modified ZnO exhibited low toxicity in sprouts, with 0.89-fold upregulation of citrate in central carbon metabolism. This contributed to providing energy for resistance to NP stress through amino acid and carbon/nitrogen metabolism, accompanied by changes in membrane properties. Notably, smaller-sized and hydrophobic NPs intensely stimulated the release of root metabolites, forming corona complexes with exudates. The hydrogen-bonded wrapping mechanism in protein secondary structure and hydrophobic interactions of heterogeneous functional groups drove eco-corona formation, along with the corona evolution intensity of n-ZnO > s-ZnO > b-ZnO based on higher (α-helix + 3-turn helix)/β-sheet ratios. This study provides crucial insight into metabolic and eco-corona evolution in bionano fates.

Stability analysis for stochastic nonlinear systems with state-dependent switching and time-delay

The stability of stochastic nonlinear systems with time-delay and state-dependent switching is studied in this paper. Firstly, system maximal solution is constructed and further extended as the global solution under certain mild conditions. Secondly, several Krasovskii-type stability and Razumikhin-type theorems are proposed by uniformly asymptotically stable functions (UASFs). These stability criteria overcome some stringent constraints associated with Lyapunov functional/functions. Finally, the theoretical findings are validated through two simulation examples.

Democratising complex system modelling

In the contemporary context of an acute need for sustainability and swift response to imminent crises such as global warming, pandemics and economic system disruptions, the focus on responsible decision making, ethical risk assessment and mitigation at all organizational levels is an overarching goal. Our aim is to introduce a deterministic method for investigating the stability of complex systems, in order to find the most important elements of such systems and their impact on different scenarios. The novelty of the current approach lies in its compact format and intuitive nature, designed to accommodate a limited amount of computational resources. The proposed modelling method involves the mapping of complex systems from a diversity of disciplines (economic markets, resource management domain and the community impact of suburbanisation) onto a sequence of chemical reactions and involving a subsequent mathematical analysis. Mapping the results back onto the use cases shows that one can retrieve a considerable amount of detail, making the modelling strategy general enough to be adaptable and scalable while also detailed enough to provide valuable insights for practical scenarios.

Fixed-time stabilization of underactuated cart-pendulum system based on hierarchical sliding mode control method

Fixed-time stabilization of underactuated cart-pendulum system based on hierarchical sliding mode control method

Stabilization of a 4D financial system with disturbance and uncertainty by UDE-based control method

The stabilization of the 4D financial system involving the external disturbance and uncertainty is investigated extensively. Firstly, two types of controllers (us) are proposed to stabilize the nominal 4D financial system which is not impacted by the external disturbances. Secondly, three kinds of filters are designed, based on which, three categories of uncertainty and disturbance estimators (uude) are presented and used to asymptotically counteract the lumped disturbance and uncertainty (ud), i.e., buude=−uˆd→−ud, as t→∞, where uˆd is the estimate of ud and b is a known vector. Consequently, the stabilization problem of such a system is implemented by the combined controllers (u=us+uude). It is noted that the obtained controllers are single input controllers, and thus easy to be implemented in applications. Finally, the proposed theoretical results are demonstrated and verified by the computer simulation.

Stability of nonautonomous systems on Fréchet spaces

Stability of nonautonomous systems on Fréchet spaces

Unified Sufficient Conditions for Predefined-Time Stability of Non-Linear Systems and Its Standard Controller Design

This paper presents a unified Lyapunov-based predefined-time stability theorem that includes three sufficient conditions. The standard theoretical analysis method for achieving predefined-time stability of non-linear systems using this theorem is provided within the framework of Lyapunov theory. The developed Lyapunov-based theorem facilitates the establishment of equivalence between the existing Lyapunov theorems concerning predefined-time stability. Furthermore, when the presented sufficient conditions are relaxed, the predefined-time stability conclusion for non-linear systems degenerates into a finite-time one. Consequently, a standard non-singular sliding mode control framework based on the unified Lyapunov-based theorem is developed for a Lagrangian system to ensure its predefined-time stability. Exemplary numerical simulation results are subsequently given, in order to illustrate the convergence behavior of the system states and confirm that the controlled systems are predefined-time stable.

Effects of salinity on glycerol conversion and biological phosphorus removal by aerobic granular sludge

Industrial wastewater often has high levels of salt, either due to seawater or e.g. sodium chloride (NaCl) usage in the processing. Previous work indicated that aerobic granular sludge (AGS) is differently affected by seawater or saline water at similar osmotic strength. Here we investigate in more detail the impact of NaCl concentrations and seawater on the granulation and conversion processes for AGS wastewater treatment. Glycerol was used as the carbon source since it is regularly present in industrial wastewaters, and to allow the evaluation of microbial interactions that better reflect real conditions. Long-term experiments were performed to evaluate and compare the effect of salinity on granulation, anaerobic conversions, phosphate removal, and the microbial community. Smooth and stable granules as well as enhanced biological phosphorus removal (EBPR) were achieved up to 20 g/L NaCl or when using seawater. However, at NaCl levels comparable to seawater strength (30 g/L) incomplete anaerobic glycerol uptake and aerobic phosphate uptake were observed, the effluent turbidity increased, and filamentous granules began to appear. The latter is likely due to the direct aerobic growth on the leftover substrate after the anaerobic feeding period. In all reactor conditions, except the reactor with 30 g/L NaCl, Ca. Accumulibacter was the dominant microorganism. In the reactor with 30 g/L NaCl, the relative abundance of Ca. Accumulibacter decreased to ≤1 % and an increase in the genus Zoogloea was observed. Throughout all reactor conditions, Tessaracoccus and Micropruina, both actinobacteria, were present which were likely responsible for the anaerobic conversion of glycerol into volatile fatty acids. None of the glycerol metabolizing proteins were detected in Ca. Accumulibacter which supports previous findings that glycerol can not be directly utilized by Ca. Accumulibacter. The proteome profile of the dominant taxa was analysed and the results are further discussed. The exposure of salt-adapted biomass to hypo-osmotic conditions led to significant trehalose and PO43−-P release which can be related to the osmoregulation of the cells. Overall, this study provides insights into the effect of salt on the operation and stability of the EBPR and AGS processes. The findings suggest that maintaining a balanced cation ratio is likely to be more important for the operational stability of EBPR and AGS systems than absolute salt concentrations.

A Simple Controller Design for a Class of Uncertain Nonlinear Control Systems Guaranteed to Achieve Arbitrary Exponential Convergence Rates

This paper first proposes the concepts of high-efficiency stabilizable systems and high-efficiency controller. Then, using the time-domain analysis methodology, it is proved that a class of uncertain nonlinear systems can indeed become high-efficiency stabilizable systems under certain conditions; at the same time, we also provide its corresponding high-efficiency controller. Finally, some numerical simulation results are offered to illustrate and demonstrate the correctness of the main theorem and the design process of such a high-efficiency controller

Advancing therapeutic efficacy: nanovesicular delivery systems for medicinal plant-based therapeutics.

The utilization of medicinal plant extracts in therapeutics has been hindered by various challenges, including poor bioavailability and stability issues. Nanovesicular delivery systems have emerged as promising tools to overcome these limitations by enhancing the solubility, bioavailability, and targeted delivery of bioactive compounds from medicinal plants. This review explores the applications of nanovesicular delivery systems in antibacterial and anticancer therapeutics using medicinal plant extracts. We provide an overview of the bioactive compounds present in medicinal plants and their therapeutic properties, emphasizing the challenges associated with their utilization. Various types of nanovesicular delivery systems, including liposomes, niosomes, ethosomes, and solid lipid nanoparticles, among others, are discussed in detail, along with their potential applications in combating bacterial infections and cancer. The review highlights specific examples of antibacterial and anticancer activities demonstrated by these delivery systems against a range of pathogens and cancer types. Furthermore, we address the challenges and limitations associated with the scale-up, stability, toxicity, and regulatory considerations of nanovesicular delivery systems. Finally, future perspectives are outlined, focusing on emerging technologies, integration with personalized medicine, and potential collaborations to drive forward research in this field. Overall, this review underscores the potential of nanovesicular delivery systems for enhancing the therapeutic efficacy of medicinal plant extracts in antibacterial and anticancer applications, while identifying avenues for further research and development.

Early fault detection for rolling bearings: A meta‐learning approach

AbstractEarly fault detection (EFD) of rolling bearings aims at detecting the early symptoms of faults by monitoring small deviations of health states. Accurate EFD enables predictive maintenance and contributes to the stability of mechanical systems. In recent years, machine learning based methods have shown impressive performance on EFD. Most of the current machine learning‐based methods assume the availability for a large amount of data. However, in practice, the authors may only have a very limited amount of training data, which makes it hard to learn a reliable machine learning model. To address this concern, in this work, the authors propose to tackle EFD via meta learning. Specifically, the authors first formulate EFD as a few‐shot learning problem and then propose to tackle this problem with a metric‐based meta learning method. Furthermore, ensemble learning is further leveraged to improve the detection robustness. For the proposed method, the distribution difference from the working conditions and the bearings are considered. The experimental results on two bearing datasets show that the proposed method can achieve better EFD performance, that is, detecting incipient faults earlier while bringing in lower false alarms, compared with several frequently used EFD methods.

The levitation force and stiffness enhancement of single domain GdBCO bulk superconductor by an axial background magnetic field

How to improve the levitation force (FL) and its stiffness between a permanent magnet and a REBCO bulk superconductor is one of the most key and attractive problems to be solved for practical applications. In this paper, we provided a novel hybrid magnet added superconductor system (HMS) to enhance the levitation force and the stiffness, the HMS sample is assembled by a single domain GdBCO bulk with an attached permanent magnet (PM) serving as an axial background magnetic field. The results indicate that (1) the FL increased first and decreased then with the increase of the PM diameter (dPM), the largest FL is achieved when the dPM approaches the diameter of the GdBCO bulk, FL has been improved up to 152% with a thinner PM; (2) the FL increased with the increase of the PM thickness and saturated at a certain value, FL have been improved up to 168% with a thicker PM; (3) the stiffness of FL has been improved up to 187% and 201% with the increase of the PM diameter and thickness; (4) the FL and its stiffness enhancement dependent on the positive trapped field of the field cooled HMS samples. The results are of great significance to improve the performance and stability of maglev systems, the mechanism for enhancing the levitation force and stiffness property has been investigated in details.

Implementation of modified P&O and an adaptive fuzzy logic controller based MPPT tracking system under partial shading and variable environmental conditions

Most of the conventional Maximum Power Point Tracking (MPPT) Algorithms provide the finest efficiency during uniform irradiation conditions, but under variable irradiation or partial shading condition (PSC), the performance deteriorates and the solar PV system is unable to provide the maximum electricity out of the PV Modules. This degradation in performance occurs due to the presence of numerous local maximum power points (LMPP) and a single global maximum power point (GMPP) in the power versus voltage (P-V) characteristics and the perfect tracking of these LMPP is not possible with the prevailing MPPT algorithms. In order to eradicate this shortcoming, we have proposed the implementation of an adaptive Fuzzy Logic Controller (FLC) based on Perturb and Observe (P&O) technique by employing a boost converter with variable resistive load under uniform irradiance condition (UIC), dynamic atmospheric conditions (DAC) and PSC in this article. We also demonstrated the usage of a simple and improved P&O algorithm by employing a buck boost converter for faster tracking time. These two suggested approaches of FLC and P&O incorporate a variable load scenario and a stable load scenario respectively to address the problem of output voltage oscillation in a PV-based system. The FLC is designed to adjust the dynamic change in step size based on the rate of change of the yield power of the PV panel to reduce oscillations in output of the boost converter and the PV system. According to the results of this analysis, the recommended FLC-based P&O (FLC-P&O) algorithm outperforms the proposed P&O algorithm under DAC and PSC with respect to tracking speed, steady-state error, and dynamic response. Apparently, it can be concluded that the proposed FLC-P&O technique can be applicable to real-time systems for reliable and efficient operation of the boost converter and add to the stability and simplicity of the contemporary PV-based systems.

Electrical measurement method of static friction force on rough surface

Friction plays a key role in the assessment of the safety and stability of mechanical systems (such as superconducting magnet quench explosion, aerospace vehicle bearing wear, etc.). Due to the closeness of the interfaces in engineering structures and the randomness of the contact surfaces, existing methods for measuring static friction force are unable to measure it at the contact interfaces of engineering structures under service conditions. In this paper, a new method for measuring the static friction force at the interface based on electrical signals is proposed. This method enables the measurement of the static friction force at interfaces of complex engineering structures under service conditions solely through electrical signals. The results indicate that the contact resistance gradually decreases with the increase in tangential load during the static friction stage until a monotonic behavior of macroscopic sliding occurs. The evolution of contact resistance is linked to the evolution of the real contact area, and this monotonic behavior can be explained as the deformation form of contact points. The accuracy of the proposed electrical measurement method is verified by comparison with experimental results (with an error of less than 9%). The indirect measurement method of friction force proposed in this paper can effectively measure the static friction force at the interfaces of engineering structures under service conditions, and it is expected to be applied to the detection of friction performance at engineering structure interfaces in extreme service environments.

Hybrid Observer-Based Asymptotic Stabilization of Non-Uniformly Observable Systems: A Case Study

Hybrid Observer-Based Asymptotic Stabilization of Non-Uniformly Observable Systems: A Case Study

Explicit stability condition for delta fractional order systems with [formula omitted]

This paper delves into the stability of time-advance delta fractional order systems, with a specific emphasis on the order range (0,+∞) rather than the conventional range (0,1). The delta Laplace transform is used to investigate the stability of the suggested system, and a mapping relation ρ=ss+1 is introduced. The explicit stability condition is provided, articulated in relation to a specific distribution of eigenvalues of the system matrix. To validate this condition, the paper establishes equivalence between the delta difference and the nabla difference. Furthermore, both quantitative and qualitative analyses are conducted on the range of the unstable region. Finally, the correctness of the developed results is validated by three examples.

Iterative learning control of an Euler-Bernoulli beam with time-varying boundary disturbance

This paper investigates the stabilization of Euler-Bernoulli beam systems modeled by a partial differential equation (PDE) with unknown time-varying disturbance. An iterative learning controller is designed using only boundary state feedback to realize the vibration control subject to unknown boundary disturbance. The well-posedness for the closed-loop system is given by the operator semigroup theory. Furthermore, the exponentially stable for the closed-loop system is proved by the Lyapunov method. The comparisons with existing results are made to demonstrate the effectiveness and advantages of the proposed boundary iterative learning control method.

Simultaneous robust model predictive control and state estimation for nonlinear systems with state‐ and input‐dependent uncertainties

AbstractThe convergence and stability of uncertain nonlinear systems is a challenging problem in the nonlinear control area. Besides, in many practical cases, all states are not measurable and are affected by measurement noise. Based on this motivation, the first objective of this paper is to design a novel output feedback robust model predictive control approach for nonlinear systems with state‐ and input‐dependent uncertainties and measurement noise. This approach combines state estimation and robust model predictive control (MPC) into one min–max optimization and by solving the optimization, these two tasks are performed simultaneously. The studied nonlinear system comprises a linear part, a nonlinear part, and a function that denotes the state‐ and input‐dependent uncertainties. Therefore, the other objective is to reduce the computational complexity; thus, the system's nonlinear term and the aforementioned uncertainties are converted into additional disturbances. Subsequently, the optimization problem becomes a quadratic form, which leads to global convergence with the appropriate selection of objective function weights. Besides, this paper explores the convergence of the closed‐loop system states and the sufficient synthesis conditions to guarantee input‐to‐state stability. The implementation on a numerical example and a CSTR process demonstrate the applicability and reliability of the proposed approach.

Damping Characteristics Improvement of Wind-PV Hybrid System by Coordinated Optimization of SVC-POD Controller Parameters

Background: With the increasing penetration of new energy resources such as wind farms and photovoltaic power plants, there is concern about the stability of power systems. Methods: Aiming at the low-frequency oscillation issue of the wind-PV hybrid system, a coordinated optimal design strategy based on Static Var Compensator (SVC) and Power Oscillation Damping (POD) control is proposed. Modal analysis is used to locate the controller, then the Whale Optimization Algorithm (WOA) is introduced to optimize the SVC-POD controller parameters. To solve the wind-PV hybrid energy system's low frequency oscillation issues, the damping ratio and angular velocity of the generator rotor are considered in the objective function. Results: Taking IEEE four-machine two-area system as an example, several working conditions are designed, including changing the power of the contact line. The eigenvalue analysis and simulation findings verify that the suggested proposed method can successfully raise the damping ratio of the system, keep the generator speed stable, and restrain the occurrence of low-frequency oscillation. Conclusion: Simulation results demonstrate that this method efficiently suppresses the lowfrequency oscillation and increases the robustness of the system.

Asymptotical Stabilization of Logic Dynamical Systems via Output-Based Random Control

Asymptotical Stabilization of Logic Dynamical Systems via Output-Based Random Control